Pith. sign in

Paper Citation Record · LEDGER

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series

As of 7 August 2026, this Paper Citation Record lists 100 of 118 outbound references and 0 inbound Pith citation observations for arXiv:2608.04706.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.04706 v1

Coverage vector

measured 100 of 118 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:32:21.965465Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 118 outbound references displayed

  • verified exact6
  • verified fuzzy10
  • unresolved68
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch15

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe035e70-3542-41e3-a685-3dd74cc4a32d · outbound

This paper cites Wong and Christian Thomas and Patrick Halpin , keywords =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Wong and Christian Thomas and Patrick Halpin , keywords =

Reference 1

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:30.862896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:11.925799Z digest=sha256:2f49bb353d866577257355179a78516d1fdb8bdd029380cef423ba02ba04f473

Observation 0ef12f4e-d0b3-4b82-92ff-32c8dc73011b · outbound

This paper cites Soviet Physics Doklady , volume=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Soviet Physics Doklady , volume=

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.140611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.140611Z digest=sha256:226b5d352b21db1b2e4186bbe5be4905693daf70f5ef7dfff422f060417c19c5

Observation e0929866-59ff-43e2-aa9b-ec99bdd2f993 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.207783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.207783Z digest=sha256:e62b1d1835619ef57af15cc3466c7feed9ee44867a26e35e1821f19a90d1c171

Observation 3db2ccdd-4792-4936-a43c-0a6899124bc8 · outbound

This paper cites and Haberland, Matt and Reddy, Tyler and Cournapeau, David and Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and Bright, Jonathan and.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Haberland, Matt and Reddy, Tyler and Cournapeau, David and Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and Bright, Jonathan and

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.290258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.290258Z digest=sha256:35e321195bf788754436956d8b1d2569ee7c6bf44c5e6c3faadb524d02993996

Observation f69c4c04-9f72-4832-b3f9-9eed3eed7b0a · outbound

This paper cites Earth System Science Data , VOLUME =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Earth System Science Data , VOLUME =

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.355778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.355778Z digest=sha256:29f98e8c35f555c950bda736f6495fb69e227a22b8a9abf3494aa3c036aa428d

Observation 2f8662c5-2113-438f-b377-cbf89586e264 · outbound

This paper cites 2017 , note =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2017 , note =

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.422415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.422415Z digest=sha256:29e9d87f01f44efaa819a650c09f1479c785b6e6c91d013477a4496151199cf8

Observation 20af7974-b8f1-40a7-b4b1-e1215f22b148 · outbound

This paper cites Sensors , VOLUME =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Sensors , VOLUME =

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.585228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.585228Z digest=sha256:c5edc1d20178f50545c668523e71e631b655d4638491e850efa9188f7af0e31f

Observation 912f8d87-b21f-449e-8ae8-b5e96a47208b · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.714043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.714043Z digest=sha256:020fbf967e465131a2b2ec33031adcc2db114b1b0821dae401302f8be2f6cacd

Observation 0753222a-2fc9-4a57-85a3-159831e28f76 · outbound

This paper cites Entropy , VOLUME =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Entropy , VOLUME =

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:12.858608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:12.858608Z digest=sha256:db75e08899fbe617d21902a1feebb92a615e433e701668b8035856e9a35b6453

Observation e3a2b6d6-fbe3-4674-931d-9a63e02955bf · outbound

This paper cites International Journal of Remote Sensing , volume =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series International Journal of Remote Sensing , volume =

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.176929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.176929Z digest=sha256:f95c89dc89f3020b9b595f036714bbe06e07648d607a1aaf0befc2bdd2361129

Observation ca896c47-eb2d-4c2e-b0f0-74c6502ff2f2 · outbound

This paper cites GIScience & Remote Sensing , volume =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series GIScience & Remote Sensing , volume =

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.284965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.284965Z digest=sha256:9742059051f461a50bc7bc06eacc848d4d43402f038d83d7889d5bdcf62e5e16

Observation 8f17ae5c-2228-4665-b3d5-ac320f0dd5b1 · outbound

This paper cites Remote Sensing , VOLUME =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Remote Sensing , VOLUME =

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.453405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.453405Z digest=sha256:034c82e5938da48b42467094bbf432385956e8bf94f8b0f3e308e1879d9d7621

Observation 997725ee-528f-45df-829a-6fb4a4e1a4f1 · outbound

This paper cites Extraction of Offshore Wind Turbines in China by Combining Multispectral and SAR Image Data , year=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Extraction of Offshore Wind Turbines in China by Combining Multispectral and SAR Image Data , year=

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.505626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.505626Z digest=sha256:56f12f9f8ecc468c4b702802eb99e99e026b6aa3ff207011a254cd2142931a02

Observation 0beeb2be-6737-446c-be56-44177b5d4fdc · outbound

This paper cites LandTrendr — Temporal segmentation algorithms , journal =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series LandTrendr — Temporal segmentation algorithms , journal =

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.678166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.678166Z digest=sha256:736ed6b64e5483b6b59d0fbdd621d64be176d62007e5a88d703011f0e534e4c5

Observation b9f079d0-e85c-4659-9178-0537425233ac · outbound

This paper cites Geo-spatial Information Science , volume =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Geo-spatial Information Science , volume =

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.880939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.880939Z digest=sha256:c7d554bac4fac6b4dc7adc3d5144b8182d45b8496ffb267e934d0275872e4f6b

Observation 489b51a5-aaf5-4266-8f8a-47b400c0ecac · outbound

This paper cites and Matos-Carvalho, João P.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Matos-Carvalho, João P

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:13.939223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:13.939223Z digest=sha256:fafbac55ec1dc11b3ea6f5430b32d9d70b17eb846107f039ad5c5a16da59e235

Observation aa6447e4-8c11-4c4d-b0a9-5616827c7380 · outbound

This paper cites Energies , VOLUME =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Energies , VOLUME =

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:14.051084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:14.051084Z digest=sha256:1aa3a5d137b2891472c813a1200c07d0b5d676c90879848e09fda181d9b50392

Observation 1d3a15fa-1ab6-4a7d-a2c4-debf0ea09303 · outbound

This paper cites Remote Sensing , VOLUME =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Remote Sensing , VOLUME =

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:14.143295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:14.143295Z digest=sha256:57ced8311e687493eb41d34af7e02dbe12280272d3044a97191a7a77a22ae033

Observation 8a01bd6d-469d-429e-b787-107ea516cd1e · outbound

This paper cites Automatic extraction of offshore platforms using time-series Landsat-8 Operational Land Imager data , journal =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Automatic extraction of offshore platforms using time-series Landsat-8 Operational Land Imager data , journal =

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:14.431325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:14.431325Z digest=sha256:887e515e01ed212a3cd1f45f30bda12ec849f1f2bc242bfe15ed426b16d6acaf

Observation d6721851-cb48-42ce-9201-6014ef188f58 · outbound

This paper cites 2023 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2023 , issn =

Reference 29

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:28.872357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:14.596780Z digest=sha256:ffdff02886be0083f711db05c408425d3bd91a7aa0cce52fc1c20111055879d5

Observation a04246a7-f281-441c-ae9b-3a1389d53b49 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 30

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:28.598642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:14.686818Z digest=sha256:94218ad4e88f3b7908f86abfda346b31ef69a506e2f793f9c30626482249e4e7

Observation b5b0adbb-2f77-42e6-b27b-1b531d1c4925 · outbound

This paper cites 2023 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2023 , issn =

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:14.753351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:14.753351Z digest=sha256:7c6f79232b7ae6ee3d9908f55ea6878f0f5c244d97e634ab0297070bf7f7dd07

Observation 01e1ced0-2ea1-48bf-b2de-f450c5cbcf7d · outbound

This paper cites 2024 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2024 , issn =

Reference 32

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:28.332974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:14.818193Z digest=sha256:7e1b6a8b7e385a58423403dfe2ecc447f27c70b919371f5bf491b59082903e3b

Observation ce2a5942-3587-4f49-9ad0-87ba98a9cf68 · outbound

This paper cites 2025 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2025 , issn =

Reference 33

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:28.167564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:14.889846Z digest=sha256:68f23840755b5f35df18546e179a184feaf93537375d9c02afcc25565c220579

Observation 575c4f5e-fa02-462d-b0f6-1caa5179713b · outbound

This paper cites GMES Sentinel-1 mission , journal =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series GMES Sentinel-1 mission , journal =

Reference 34

Resolution
verified exact
doi, observed 2026-08-06T18:32:24.084543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:14.988459Z digest=sha256:d5f8dfeb1c4678174073b79259341f06634edd3ae91d2a0796b7de927bc3d854

Observation 1d5cc88f-bb67-46ac-97d5-ede7ff7590ab · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.060257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.060257Z digest=sha256:74f5c68587806bb8cf763c00665338aa1babaae6c0c89ff6b12e3e6e50b7a7ff

Observation 7f2ce4df-a373-44a6-b3c3-71ab45b479e9 · outbound

This paper cites and Porchetta, S.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Porchetta, S

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.134754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.134754Z digest=sha256:672b8f9cad5c6c831539602cdf495d38109131c0b8b81e766519164f32434f75

Observation 060a089a-78c7-473e-a432-29fe8b237570 · outbound

This paper cites 2024 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2024 , issn =

Reference 37

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:27.899702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:15.230171Z digest=sha256:cf219613477dd4a4f1bcda06bc95750ceb193629fe95bc1c03817b058a11ade6

Observation 195720f8-7df9-4b94-bb37-c9d64c6fc15a · outbound

This paper cites 2025 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2025 , issn =

Reference 38

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:27.563154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:15.335280Z digest=sha256:7bc811aa28d5e9eeafab7d7906f06b19ded113315a85f0c3a71b36604e2fcc84

Observation 5d75ae6f-1c98-4b13-aaea-80b30db2355f · outbound

This paper cites 2022 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2022 , issn =

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.431602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.431602Z digest=sha256:b5af8a32d0ff5a4b5a6bf2944cabfafbf87bf8a7a229ca284f31ed1e0ae18bf9

Observation d0457484-5e73-44d2-83f3-b9243772b64c · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , year=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , year=

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.491544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.491544Z digest=sha256:17fa97dc4bc1f32ea5921c0563468c19dfed0deea1d92c3d7638e0aa4797bc90

Observation f944a3ea-7329-44f1-8dff-972f3e7906ab · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series YOLOv10: Real-Time End-to-End Object Detection

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.588637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.588637Z digest=sha256:214f4afe95b93edaefa2582e2e19c40fa7b546446b34ed1c51cdee956e1ccd13

Observation c4367fe8-3f47-4d13-bbe6-f968e2ef8669 · outbound

This paper cites Journal of Renewable and Sustainable Energy , volume =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Journal of Renewable and Sustainable Energy , volume =

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.663672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.663672Z digest=sha256:fbf8fe3ab137f8412644be04ef25c119697225191e2af4f3b46cca88aa7f8dc6

Observation 9303de05-f406-4c63-b324-81a4fb403223 · outbound

This paper cites Emergence of floating offshore wind energy: Technology and industry , journal =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Emergence of floating offshore wind energy: Technology and industry , journal =

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.771060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.771060Z digest=sha256:028f8e463b2655b5493f61c89ae9e7584548c3a8e59088c4bb1944c66bf54dbc

Observation cc64a9fa-8953-40b6-a4f1-bb7e2b66bc1c · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.837829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.837829Z digest=sha256:22601c041faf1c3566e7ff5b5744a524dfa01b8cd12f4ca32a44660ddbbb002a

Observation e2f7c788-e171-45d8-9038-dea66fb4b95e · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:15.946866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:15.946866Z digest=sha256:c9677c375f511d0ee5af94b3a0725b2361f1304ec4906b230d62d3d5e455ff24

Observation fc942d30-0547-4910-b288-152b59638b0c · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.010452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.010452Z digest=sha256:1c82c24f8e0ff33fdbfad1e9b103362669c01212884cde071b5d07cfaa75bf01

Observation 6770dc23-51bb-4869-aab8-fe667955f7eb · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.083085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.083085Z digest=sha256:30ed5c321e71df65845740faa8acfe37234f48a93853baea0bbd3edbf7791e06

Observation a3051db0-b436-4f16-ac4d-172c4598483e · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.130146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.130146Z digest=sha256:1fe771256b8ae5e1f8eb6a1f53d9f0221b5f6804aa1a9f199ec3f3634d39c42a

Observation 07534156-6e3d-4cff-9269-4c1fbb335798 · outbound

This paper cites An innovative platform for exploring the Earth , howpublished =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series An innovative platform for exploring the Earth , howpublished =

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.204397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.204397Z digest=sha256:ca536668bb3568c7399b57d6c29e6a37e1adcc4213491a283be0a98d32f012a6

Observation 1747830f-2bae-4365-bdd3-476ea2e2c4cd · outbound

This paper cites and Bachofer, F.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Bachofer, F

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.295725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.295725Z digest=sha256:cccab1bce50d307e3db5c44dbb46527740d919d2afdb0cacdb6ebd666773e5ed

Observation e999b32f-f9f7-4d44-88dd-8ecaa1e5aa6b · outbound

This paper cites and Kuenzer, C.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Kuenzer, C

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.373697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.373697Z digest=sha256:5c2e704313c47908f53f589c4da78264c2492f1f4f8e54ef9f0aba719bd0fc1e

Observation c9579499-4477-4671-922d-82d8161faaf3 · outbound

This paper cites doi:10.5281/zenodo.18735421 , url =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series doi:10.5281/zenodo.18735421 , url =

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.442311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.442311Z digest=sha256:57781e50bc5b42e6713cc0539429260cab8043f4e7b4c034253143e42173ea67

Observation d8000b61-ea1c-49bd-b86a-4e30e3d8f8c8 · outbound

This paper cites Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on , pages=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on , pages=

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.530795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.530795Z digest=sha256:1786c746f2bd5ab249283b6a49a36cbf79e805949ccf018d5b856dd972fcae13

Observation 4086d033-7996-46b2-a12a-c6711f90b6f0 · outbound

This paper cites Soft Computing and Pattern Recognition (SoCPaR), 2014 6th International Conference of , pages=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Soft Computing and Pattern Recognition (SoCPaR), 2014 6th International Conference of , pages=

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.612550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.612550Z digest=sha256:ff6f42a6d6f2e2ce4e9e3521d2b17d57c4e6791db799d2013a92d9d13d63928f

Observation 3cbf47ba-3946-4e07-9f61-633c212309d0 · outbound

This paper cites Advanced Data Mining and Applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12-15, 2016, Proceedings 12 , pages=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Advanced Data Mining and Applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12-15, 2016, Proceedings 12 , pages=

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.701347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.701347Z digest=sha256:2be8e870c38c1ecf7bf73b07a739dd23394444444e5bc3935f30998635bdd97b

Observation 6c93612e-100c-4408-8f2c-9c1d170fda24 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:16.760663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.760663Z digest=sha256:1ebe51e743bca3b4b7f09db5d7f5fa49a8d312d64fa5e01b8e866d8c4e4573fb

Observation d4a70765-14f3-4d41-b479-b23b015d5fab · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 58

Resolution
parse uncertain
no resolver link, observed 2026-08-06T18:32:16.925465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:16.925465Z digest=sha256:d80d18f15e1d025bfad890fcc41639424cd671cfe76aa5bf0e900494c6618be8

Observation abbc1ffe-13a0-4a2b-9677-359ebf4a521f · outbound

This paper cites 2025 , howpublished =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2025 , howpublished =

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.013882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.013882Z digest=sha256:1d39cb015340371e970d25b91538b1406e9cfc4e4a06d830d3d87686ea8ec32f

Observation a462ef92-9be8-4246-94e4-f121bfa6e425 · outbound

This paper cites The Journal of Supercomputing , year =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series The Journal of Supercomputing , year =

Reference 62

Resolution
verified exact
doi, observed 2026-08-06T18:32:23.893761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:17.238712Z digest=sha256:368b0024fae7de4d07438c2b954a012d92a607a82b023b1755001634cc338276

Observation ced6f498-02ee-47d5-af2f-72dbebf4ff30 · outbound

This paper cites A Review of Deep Learning Models for Time Series Prediction , year=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series A Review of Deep Learning Models for Time Series Prediction , year=

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.388067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.388067Z digest=sha256:dd150473a4d6d6f9467b2a638c7b4bccb863d4830854e2060aa5914bd92db00b

Observation 1d715c86-02fd-47ed-97e5-8d8fd29ad84b · outbound

This paper cites LSTM can Solve Hard Long Time Lag Problems , url =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series LSTM can Solve Hard Long Time Lag Problems , url =

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.549716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.549716Z digest=sha256:3c06a4cb63ced33b58a13d67efde5c1125da8fd8962c3dfc76180b9b2f913f7d

Observation 4608526a-a969-4b0c-86c2-1a9aa99dd364 · outbound

This paper cites , journal=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series , journal=

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.607533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.607533Z digest=sha256:f840f84480cd0b7249522e8d5a4f9f9f8ba1b4022c7a94695951f47e4f7bc23a

Observation 7009aafc-0d48-4da6-93ce-25222cc1267e · outbound

This paper cites , journal=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series , journal=

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.615096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.615096Z digest=sha256:6274d7bce145f02abe270460b853113bd45171cc230e776fefdd1eed16b0be6f

Observation 37d71507-079e-42f9-81cf-a8064471bbf9 · outbound

This paper cites 1990 , issn =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 1990 , issn =

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.650333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.650333Z digest=sha256:f2e4892823958bed209cb14467339ecb00a78cf1cb23244ded0487099a9df6f8

Observation eb22c92d-ef28-40d4-9dcf-15eb7c0ac29e · outbound

This paper cites and Kaiser, Lukasz and Polosukhin, Illia , title =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Kaiser, Lukasz and Polosukhin, Illia , title =

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.694682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.694682Z digest=sha256:051fbb0ed512701ffd1890205266e468bdd3d9fa05e7b12fafcef4eb30c321bd

Observation 9f2c6776-ec6a-4e7a-a884-5c9ebb81489e · outbound

This paper cites and Paliwal, K.K.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series and Paliwal, K.K

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.763084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.763084Z digest=sha256:7b1285e8dc82d008c3d6eddfba54dbe0d1405f9c8dbe6ea62a447d91398681f7

Observation 9073276e-d209-4677-8136-6c03d1706775 · outbound

This paper cites Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) , year =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) , year =

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.818540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.818540Z digest=sha256:c5d5c23da89c84148bcff801b6f634f4fbc3bf8869e9ad0e446f26a462a96a64

Observation af6bc176-9085-4f77-824b-d96fde685536 · outbound

This paper cites 2018 , howpublished =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2018 , howpublished =

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:33.359837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:17.875631Z digest=sha256:7a33e31eaaf7d8a3312a7f9e51c22aa6d401aa3a4fb05f0787972ddc94ee808b

Observation db6889e1-2b68-4bda-be57-8a1fc0193327 · outbound

This paper cites Language Models are Few-Shot Learners , url =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Language Models are Few-Shot Learners , url =

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:17.946116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:17.946116Z digest=sha256:bbfcc44ee6fbaef56a1601a4fecc7f600d9df589d91b444ce146143f1bfd1f83

Observation 17c83a85-b9c8-462e-89d2-1fbee978f3b6 · outbound

This paper cites Learning Complex, Extended Sequences Using the Principle of History Compression , year=.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Learning Complex, Extended Sequences Using the Principle of History Compression , year=

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:33.177394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:18.076158Z digest=sha256:873ae9b88658240c3f1457b62a05ed4e12cb44d0acacb123192b9e8f75d7d0e4

Observation d60df56c-8e15-4a47-a655-27b9466fc22e · outbound

This paper cites 2024 , eprint =.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series 2024 , eprint =

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:32.991188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:18.322249Z digest=sha256:4e7d6022412e2eaaea996f4ce6abbcefda336ea34fbaa4abdb1169d87405b564

Observation b43e5baa-94c9-4e30-b3f5-e39498208323 · outbound

This paper cites Akhtar, B.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Akhtar, B

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:19.196143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:19.196143Z digest=sha256:f0dce6215298c02530ed52526aa242f75fe8ebeab7192a3f0bcc6f91dea98bf6

Observation 270fd56b-cda7-44d6-bced-f0107ded8bf5 · outbound

This paper cites Brown, B.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Brown, B

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:32.758038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:19.255618Z digest=sha256:252cfd5b6a1d7ec6247a3870dc054655b04a29f5c27323b1547538d7bff8bec0

Observation 9d72cc4e-f50c-4319-a2f6-0bb0e54cd7a6 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:19.341063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:19.341063Z digest=sha256:abb9d672cf78ec024ffbebdca91baddf1a5a6b7bcf3ad0fa1fa05bf70e71a986

Observation 5d3c134d-d846-4102-8536-c581c717cfca · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:19.409162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:19.409162Z digest=sha256:9391b0ddb4504a0414b663c679620afe6edae73b1775285b8a57e824bb9bd5b0

Observation 84a1ae47-43e2-471a-9b87-8c22faac4772 · outbound

This paper cites Djath and J.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Djath and J

Reference 99

Resolution
verified exact
doi, observed 2026-08-06T18:32:23.663153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:19.478057Z digest=sha256:9978a76784fd2fab06f03fc26400ca22590d9f39ba8a3b053f1a2a8729953e04

Observation b3c774a0-1ab2-484d-8dcb-e28eeef46e0a · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:19.571412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:19.571412Z digest=sha256:aaea653ee7f9b31cbfd15d7563c00a24cc437c3d366cf1a6c5b4f528adb096f6

Observation 5a6f8153-02b4-460e-801c-58b2821da6f8 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:19.633750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:19.633750Z digest=sha256:073b92f3eab5f5c4d9b0a90fdba27a65996691e16fabbb6e15eb77ab2b9a21d9

Observation 6251649e-4951-48ea-af9f-bd14275dd804 · outbound

This paper cites EnBW he dreiht: First wind turbine installed.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series EnBW he dreiht: First wind turbine installed

Reference 102

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:32.595659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:19.746845Z digest=sha256:1d44089130fb6b52ea39333d56c383c8b5211c9b2b51e24cc909d1a73b8716c5

Observation ddaec2f2-895f-4148-b5cd-050d97fc9bf3 · outbound

This paper cites An eu strategy to harness the potential of offshore renewable energy for a climate neutral future.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series An eu strategy to harness the potential of offshore renewable energy for a climate neutral future

Reference 103

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:32.455289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:19.812503Z digest=sha256:79ca30efe43f67aa6aaad3d7dbc08e0e69279372b885ea50e9eb4be64c1037c8

Observation 93719d8b-7164-4677-8c63-d6aa404f4050 · outbound

This paper cites Union of the esri country shapefile and the exclusive economic zones (version 4).

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Union of the esri country shapefile and the exclusive economic zones (version 4)

Reference 104

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:32.265985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:19.913591Z digest=sha256:8267f447cb2f374409fda2f02c1400a53d80a79aa80d24f3f8f1b4270931ee8d

Observation d2f06a21-54d9-4139-83f8-826433248ff9 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 105

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:19.990475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:19.990475Z digest=sha256:ce010fecfa085fb0c3f9d5115acabc60db725c9b6cd01c934971562b9c633e01

Observation cca61b37-e0fc-4e66-9300-717429445bbb · outbound

This paper cites Download data | global energy monitor.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Download data | global energy monitor

Reference 106

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:32.084248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.059241Z digest=sha256:869022fdb2d26853a2d0ca3366153a8436885e6e6ac45b73aac8d2bfbeae2470

Observation a9c9da44-2331-42b6-aaf8-ca456f6fda56 · outbound

This paper cites Graves and J.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Graves and J

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:20.121801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:20.121801Z digest=sha256:84b45e65a35a2973ef782f2b3671eb4744bac0675c4891892da1a6711627fb9b

Observation 7c048305-e0f3-40c7-b929-bec9af6519e9 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 108

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:25.318870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.179613Z digest=sha256:5811298f9dfc963b258817d6fc069d454de5fd84b1e2f58c191e2bf1e88bfe94

Observation 0de55ba7-3338-4f9a-98a0-53e5a65f1f68 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 109

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:30.567517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.268640Z digest=sha256:e40891b5c7306f0809fb067848e4cdf0b3e90050fae0027396c4a601b27d92ea

Observation 08cbddd8-8019-429b-9aec-7eeb456d087c · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 110

Resolution
verified exact
doi, observed 2026-08-06T18:32:23.541545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.333311Z digest=sha256:cad4c3799f280144b5a4e570d24cd70e897a4878f7486b2d32f81ff8424b1a07

Observation 03efa657-038a-41bf-87f9-d44eb8792889 · outbound

This paper cites Hochreiter and J.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Hochreiter and J

Reference 111

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:31.874066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.431057Z digest=sha256:55fc3ada92bfe90afaff89f98a82932ad9d83219fee9e317b12a149f7e529a5a

Observation 25ef6b67-572a-4d45-93e6-e8fb2f17d618 · outbound

This paper cites Hochreiter and J.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Hochreiter and J

Reference 112

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:20.503469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:20.503469Z digest=sha256:ad0b0847aad02ea4b0a77801b28c710da12b05caceede652c39e058dc8d25954

Observation 10f4eb81-7f2e-4f35-a640-7b7af671fadd · outbound

This paper cites Hoeser and C.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Hoeser and C

Reference 113

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:30.064470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.587829Z digest=sha256:2ba5cc0b87e06eb480e88af2b69ff9dce4cdc94b80e40308751dd001d84bcb32

Observation c4fb4440-0677-4141-a8a1-c7237d502c06 · outbound

This paper cites Hoeser, S.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Hoeser, S

Reference 114

Resolution
verified exact
doi, observed 2026-08-06T18:32:23.437401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:20.667606Z digest=sha256:6482326a2e60ee82256f6b467cb3d210b3db2555d359a5d072a0de5b5eb7409c

Observation 2e1e1f3c-da79-4af3-8013-ca789b7c5a9f · outbound

This paper cites Hoeser, F.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Hoeser, F

Reference 115

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:20.733078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:20.733078Z digest=sha256:177e51ed7185938b2f83be2df1385307cd937c900ac66a29e84c873da3b1baa4

Observation 6a8f3458-dc4d-4170-b79f-456f1454db90 · outbound

This paper cites Howard and S.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Howard and S

Reference 116

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:20.810693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:20.810693Z digest=sha256:72d6715df83284b18ce0649c74d91e41fe7bf4a9f417a096c81ba58b2918bf88

Observation 973d2d40-dacf-4e46-a3cc-c822239cc80c · outbound

This paper cites Ismail Fawaz, G.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Ismail Fawaz, G

Reference 117

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:20.876715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:20.876715Z digest=sha256:dc6a1d4721b60b083224d7a976fd083bbc62a1e515e88b27cccaaaabb452adbf

Observation bab33724-6734-4763-a763-a0c94913e1c2 · outbound

This paper cites Lai, C.-Y.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Lai, C.-Y

Reference 118

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:20.938744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:20.938744Z digest=sha256:a7ad73e83434cca82bac972be069dcf47f7bdad663dda15e628bc8082b7e8c90

Observation e0adee4d-9439-41f8-915b-fb8584c92d33 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 119

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:32:31.699770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.033578Z digest=sha256:e8c4485eb4b283a7d383b4af87a4e4298ad521e03816a02c5c4330cf48b3156b

Observation 47acd1d2-5806-44c0-a68d-bee48d60a889 · outbound

This paper cites Lin and Y.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Lin and Y

Reference 120

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:26.963133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.087030Z digest=sha256:8045cbbdb5bc06c19f4b4b9dbe3ec174bab3ec6d150a4babe86876e0626921a0

Observation e87fba3a-8138-4bc2-b1a2-3f55eac7d601 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 121

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:30.392175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.159083Z digest=sha256:b9fc6e19118c4cd5bd3551229cf85e892c8e1f1e6b57598a1499199dc4355af9

Observation fb61407d-08fe-4159-926a-0b2e4bfb6128 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 122

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:29.761669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.223195Z digest=sha256:10a49846e2e933e2f3f73a0968c8e62c21654059c4e48aab4a1da2b8cd9ae80d

Observation b0943437-c151-4da5-9ef7-43f79323fc14 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 123

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:21.268061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:21.268061Z digest=sha256:5f0e45297b037650cf499252c637df2e3db08d28f71669e93f4ba38a73f4161d

Observation fc6c6e81-8db5-4a49-9284-ead496dc9f5e · outbound

This paper cites Decoupled Weight Decay Regularization.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Decoupled Weight Decay Regularization

Reference 124

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:21.357168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:21.357168Z digest=sha256:6173e6ca466471c6c93dd8236e61819b067174fe30eb29ea28aee866ae85f74d

Observation 4397a144-8404-4993-9f04-6a3a28adff06 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 125

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:25.803218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.412421Z digest=sha256:5bd5c083884645a70478bb9a5e17d352a82039d9380edcfac2457c2333571956

Observation 51c61768-ba40-4ece-954a-3734d3f1d414 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 126

Resolution
verified exact
doi, observed 2026-08-06T18:32:23.772512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.484333Z digest=sha256:cbeaddb2d7e3c62efa24a1333cb8d3371008f1dc14d31c18b6daea68e6088755

Observation 2da1a8fb-dc63-4e96-9ef6-2213a92792be · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 127

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:21.554396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:21.554396Z digest=sha256:755eec614f6118fae4c15e557e2cc43d6e6b148a8f60d373ddf7b87514a49f28

Observation 640dc354-dff5-4579-a985-5430769512b9 · outbound

This paper cites an unresolved cited work.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Unresolved cited work

Reference 128

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T18:32:26.492079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.642831Z digest=sha256:c344fea0d8e571c573a3b597001c500fcb5a42f2343dae2c43a3e3c911f87191

Observation c22ac76c-e6a1-4b83-8a26-5657eb67c293 · outbound

This paper cites Radford, K.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Radford, K

Reference 129

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:32:31.537432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:32:21.690422Z digest=sha256:3b4f74f6cb9121c5d5257d86d79144472d0de12cb4818a78497c5314ec67f9a3

Observation 807d39ec-c838-4672-bb94-08d6f7250c75 · outbound

This paper cites Rußwurm and M.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Rußwurm and M

Reference 130

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:21.799391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:21.799391Z digest=sha256:4b1ffcb35b28cae0d9ede75be857d40a57a8b6744f5230551759918e87103626

Observation eaefdc9f-a184-49d1-8ba0-83acdb67892a · outbound

This paper cites Schmidhuber.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Schmidhuber

Reference 131

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:21.858181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:21.858181Z digest=sha256:c58550b38522ebd5812aa118be4b96449cb63dda57b5b804cb5a75c3fd1c7654

Observation b307fb0b-8882-42db-a3af-eb2bee733a2b · outbound

This paper cites Schuster and K.

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series Schuster and K

Reference 132

Resolution
unresolved
no resolver link, observed 2026-08-06T18:32:21.965465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:32:21.965465Z digest=sha256:cf1400365ea00a438d143eb0482ce4271034461e0075fbf4b78b787e5ef96a35

Pith citing papers

No inbound Pith citation observations are available.