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Paper Citation Record · LEDGER

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection

As of 22 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2504.13748.

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

pith.paper-citation-record.v1
2504.13748 v1

Coverage vector

measured 67 of 67 reference resolution

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measured 67 of 67 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

67 of 67 outbound references displayed

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Outbound references

Observation 09e357a2-2789-4f10-a841-313ba997abe3 · outbound

This paper cites Review Article Digital Change Detection Techniques us- ing Remotely-Sensed Data,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Review Article Digital Change Detection Techniques us- ing Remotely-Sensed Data,

Reference 1

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Observation 1a90baf2-53e7-40f5-ac57-6439d10b3ad2 · outbound

This paper cites A novel framework for the design of change-detection systems for very-high-resolution remote sensing im- ages,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection A novel framework for the design of change-detection systems for very-high-resolution remote sensing im- ages,

Reference 2

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Observation b188c437-d809-4558-910e-ff53bbdb435f · outbound

This paper cites DA2Net: Distraction- Attention-Driven Adversarial Network for Robust Remote Sensing Im- age Scene Classification,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection DA2Net: Distraction- Attention-Driven Adversarial Network for Robust Remote Sensing Im- age Scene Classification,

Reference 3

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Observation c63ad503-e4a0-4aa6-b564-38c2dfb097dd · outbound

This paper cites AMN: Attention Metric Network for One-Shot Remote Sensing Image Scene Classification,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection AMN: Attention Metric Network for One-Shot Remote Sensing Image Scene Classification,

Reference 4

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Observation b87bdb14-7e7a-4ee8-9378-377f5ef82d1b · outbound

This paper cites Landslide inventory mapping from bitemporal images using deep convolutional neural networks,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Landslide inventory mapping from bitemporal images using deep convolutional neural networks,

Reference 5

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Observation 14b3e810-5714-488e-8b31-a173f66fe2a9 · outbound

This paper cites Optical remote sensing image change detection based on attention mechanism and image difference,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Optical remote sensing image change detection based on attention mechanism and image difference,

Reference 6

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Observation dabe0816-8d62-46dc-ab9a-30c04cabd449 · outbound

This paper cites Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,

Reference 7

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Observation 2807ad91-125e-45a7-b7c8-982fc4402eca · outbound

This paper cites Updating the 2001 national land cover database impervious surface products to 2006 using landsat imagery change detection methods,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Updating the 2001 national land cover database impervious surface products to 2006 using landsat imagery change detection methods,

Reference 8

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Observation 2448331a-7753-4d98-babd-91659b77d5bb · outbound

This paper cites Remote sensing of alpine lake water environment changes on the tibetan plateau and surroundings: A review,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Remote sensing of alpine lake water environment changes on the tibetan plateau and surroundings: A review,

Reference 9

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Observation 3232fef9-9d01-4250-8a83-da1535d1ff86 · outbound

This paper cites Fully convolutional change detection framework with generative adversarial network for unsupervised, weakly supervised and regional supervised change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Fully convolutional change detection framework with generative adversarial network for unsupervised, weakly supervised and regional supervised change detection,

Reference 10

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Observation 30646659-3366-44d9-a884-60bfcb10f61e · outbound

This paper cites Change detection in multisource vhr images via deep siamese convolutional multiple- layers recurrent neural network,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Change detection in multisource vhr images via deep siamese convolutional multiple- layers recurrent neural network,

Reference 11

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Observation d2ded5ff-5501-4e14-ade2-5b1bcc5e088b · outbound

This paper cites Transunetcd: A hybrid transformer network for change detection in optical remote-sensing images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Transunetcd: A hybrid transformer network for change detection in optical remote-sensing images,

Reference 12

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Observation fa62244c-2578-4c01-8736-98145e690b39 · outbound

This paper cites Gradient-based learning applied to document recognition,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Gradient-based learning applied to document recognition,

Reference 13

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Observation bbad3ecc-8f4c-4800-b02d-00188d31fdf6 · outbound

This paper cites Attention is all you need,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Attention is all you need,

Reference 14

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Observation aee76073-e875-434d-b9f6-dd9084bdbca4 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 15

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Observation c7ab7087-f4d9-496c-8bdd-bcf6d848fafc · outbound

This paper cites On the parameterization and initialization of diagonal state space models,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection On the parameterization and initialization of diagonal state space models,

Reference 16

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Observation 17bcca45-8564-40b5-800f-cba1589977dd · outbound

This paper cites Finding structure in time,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Finding structure in time,

Reference 17

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Observation f396b27a-90f2-4c33-8476-15f9ba840d8b · outbound

This paper cites Long short-term memory,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Long short-term memory,

Reference 18

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Observation df962cbc-811b-4c0e-bd8f-2df96aaf1714 · outbound

This paper cites Deep learning,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Deep learning,

Reference 19

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Observation a1b006d6-0ee5-4a43-ad77-df52cc49060e · outbound

This paper cites Change de- tection from remotely sensed images: From pixel-based to object-based approaches,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Change de- tection from remotely sensed images: From pixel-based to object-based approaches,

Reference 20

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Observation c3462059-1ef3-469e-9774-69d37070cdfe · outbound

This paper cites Change-vector analysis in mul- titemporal space: A tool to detect and categorize land-cover change processes using high temporal-resolution satellite data,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Change-vector analysis in mul- titemporal space: A tool to detect and categorize land-cover change processes using high temporal-resolution satellite data,

Reference 21

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Observation a4328052-1acb-4959-af7a-470d2e515fab · outbound

This paper cites Ica and kernel ica for change detection in multispectral remote sensing images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Ica and kernel ica for change detection in multispectral remote sensing images,

Reference 22

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Observation 8fe05cfb-5949-4b56-9d6b-ebb44a9ea2fc · outbound

This paper cites Change detection based on artificial intelligence: State-of-the-art and challenges,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Change detection based on artificial intelligence: State-of-the-art and challenges,

Reference 23

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Observation 4c189a74-cb34-487e-b061-165d253c612a · outbound

This paper cites HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model

Reference 24

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Observation 76778f23-f78b-46fa-8a68-c59ad8ffd7bd · outbound

This paper cites Deep learning in remote sensing: A comprehensive review and list of resources,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Deep learning in remote sensing: A comprehensive review and list of resources,

Reference 25

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Observation 44ca1e5e-002c-43cd-ade7-ecfa7410c6dc · outbound

This paper cites Skysense: A multi-modal remote sensing foundation model towards universal interpretation for earth observation imagery,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Skysense: A multi-modal remote sensing foundation model towards universal interpretation for earth observation imagery,

Reference 26

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Observation 13805db3-2d25-4219-b32a-765cc157e7f7 · outbound

This paper cites Deep visual domain adaptation: A survey,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Deep visual domain adaptation: A survey,

Reference 27

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Observation 57807ceb-f537-42b1-bf4b-e7d28b8af477 · outbound

This paper cites Deep coral: Correlation alignment for deep domain adaptation,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Deep coral: Correlation alignment for deep domain adaptation,

Reference 28

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This paper cites Domain adaptation for the classification of remote sensing data: An overview of recent advances,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Domain adaptation for the classification of remote sensing data: An overview of recent advances,

Reference 29

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Observation 80554059-20f1-4d21-b625-03207aab5ed4 · outbound

This paper cites Generative adversarial networks,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Generative adversarial networks,

Reference 30

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Observation 53c7d65e-b624-4159-86c5-1548819c8805 · outbound

This paper cites Learning to adapt structured output space for semantic segmentation,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Learning to adapt structured output space for semantic segmentation,

Reference 31

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Observation 398d90b7-8002-47f0-b5be-a864a20e46b6 · outbound

This paper cites Uncertainty-guided source-free domain adaptation,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Uncertainty-guided source-free domain adaptation,

Reference 32

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Observation 17babe9a-48e6-4d9d-9912-0a8abe7ae018 · outbound

This paper cites Rdp-net: Region detail preserving network for change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Rdp-net: Region detail preserving network for change detection,

Reference 33

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Observation 6a16c6ea-1d98-463b-baf0-9edbceee7431 · outbound

This paper cites Src-net: Bi-temporal spatial relationship concerned network for change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Src-net: Bi-temporal spatial relationship concerned network for change detection,

Reference 34

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Observation ce4094e1-0ac6-43be-ac6a-faa94601fe62 · outbound

This paper cites A2dwqpe: Adaptive and automated data-driven water quality parameter estimation,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection A2dwqpe: Adaptive and automated data-driven water quality parameter estimation,

Reference 35

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raw_fallback, observed 2026-08-16T12:04:17.233984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.186500Z digest=sha256:5a9baa876b3171b3352dca15cfee3ac369539a549f94f7e7c2ca06033c9f7923

Observation 587158bd-13e1-4bad-9983-25c3efc89602 · outbound

This paper cites Visual global-salient guided network for remote sensing image-text retrieval,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Visual global-salient guided network for remote sensing image-text retrieval,

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.191208Z digest=sha256:c10d527cd7fda66a40514f994dab53d2b0ffe4dadb2ffd4c5f2265f257288ad8

Observation 3984bbc0-6994-4590-bc5a-29cacfe7e647 · outbound

This paper cites Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications,

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.196221Z digest=sha256:de67bcfc750986868b713181ff41e9d7d58c27ce6315225982bfbf8a92b83711

Observation 4bdcb63b-8435-452c-bc47-67d390749f4f · outbound

This paper cites Urban change detection for multispectral earth observation using convolutional neural networks,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Urban change detection for multispectral earth observation using convolutional neural networks,

Reference 38

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:16.202742Z digest=sha256:c67c1e7a6c7b06f56d637a9195bd565f1bb77551305c341b9850a223fc3f030b

Observation b42c6f80-c4e7-43ed-8d0b-43fded67fc54 · outbound

This paper cites Fully convolutional siamese networks for change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Fully convolutional siamese networks for change detection,

Reference 39

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source=pdf_text observed=2026-08-16T12:04:16.207496Z digest=sha256:e1e68c1d726f36e3b96012f85b303398ee295ffc23fef498a956574a7b7b3e92

Observation 1481ccc4-b9b3-40eb-8984-fab37fb298ef · outbound

This paper cites End-to-end change detection for high resolution satellite images using improved unet++,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection End-to-end change detection for high resolution satellite images using improved unet++,

Reference 40

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.212142Z digest=sha256:a1e425837fa80322808d9cca78a24ff6453c3a1e02d59b1a49dcd49962011a0c

Observation d301b0c0-e929-4725-967f-78820cb0c0a3 · outbound

This paper cites Snunet-cd: A densely connected siamese network for change detection of vhr images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Snunet-cd: A densely connected siamese network for change detection of vhr images,

Reference 41

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source=pdf_text observed=2026-08-16T12:04:16.219031Z digest=sha256:af6b266a6f9a5b88655dc8d82c44214ded42ca0a2c3c9a4ca631aa5dd62e7d9b

Observation 50fdc6c0-d72d-4c9e-96ff-f5371e844958 · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmenta- tion,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Unet++: A nested u-net architecture for medical image segmenta- tion,

Reference 42

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source=pdf_text observed=2026-08-16T12:04:16.224385Z digest=sha256:e1cc5bb911730d898bafd15b66dca73b334b848ca53eb227a2690c001c4b1e2c

Observation 2dcbb703-52fb-44b1-ac1e-5a306011c498 · outbound

This paper cites A deep multitask learning framework coupling semantic segmentation and fully convolutional lstm networks for urban change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection A deep multitask learning framework coupling semantic segmentation and fully convolutional lstm networks for urban change detection,

Reference 43

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raw_fallback, observed 2026-08-16T12:04:17.076120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.229907Z digest=sha256:2f7af44df647e14859e63656e6bd8765a7c188519e3288bdd6c2bb9069fc4c8e

Observation f64dedda-f8fe-4776-9426-9a8212fb496c · outbound

This paper cites Remote sensing image change detection with transformers,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Remote sensing image change detection with transformers,

Reference 44

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source=pdf_text observed=2026-08-16T12:04:16.235487Z digest=sha256:af9a153b83c64e0019bc7d7a86111bb9e3bb0ba41e61673d3f71741e518b0544

Observation f1b12e11-b52a-4b66-a172-8384224c5add · outbound

This paper cites Mining joint intraimage and interimage context for remote sensing change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Mining joint intraimage and interimage context for remote sensing change detection,

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-16T12:04:17.023417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.240675Z digest=sha256:9d59ea491f31cc7bcd23cd7376acc4cecc9ba2f97e70f48a0a05e2d93a57ff8e

Observation 8b9525da-9d27-4c72-ad2c-51dfbdb3da52 · outbound

This paper cites Remote sensing change detection with bitemporal and differential feature interactive perception,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Remote sensing change detection with bitemporal and differential feature interactive perception,

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-16T12:04:16.993773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.247525Z digest=sha256:db26658c7016639945060d23181181b7a7896393b135abb9ca6d49e200fac48a

Observation 6b6679ca-3414-4f73-b3f8-b7c8e86e1a64 · outbound

This paper cites Unpaired image-to-image translation using cycle-consistent adversarial networks,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Unpaired image-to-image translation using cycle-consistent adversarial networks,

Reference 47

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source=pdf_text observed=2026-08-16T12:04:16.252249Z digest=sha256:0694dd861607933db55ce971c6b7e11dad2e0fb8f432aae3ccd450322d89eae9

Observation d50874da-4cd8-4e31-b13e-1507e8da5ab5 · outbound

This paper cites An unsupervised domain adaptation approach for change detection and its application to defor- estation mapping in tropical biomes,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection An unsupervised domain adaptation approach for change detection and its application to defor- estation mapping in tropical biomes,

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-16T12:04:16.945035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.257165Z digest=sha256:68ea31bdc31c93202e3142fc334e83023bbb13f808563b92224d4ce04862af96

Observation 20f694d9-832c-4de6-a0c6-cc6a64d8e45a · outbound

This paper cites Unsuper- vised deep transfer learning-based change detection for hr multispectral images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Unsuper- vised deep transfer learning-based change detection for hr multispectral images,

Reference 49

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raw_fallback, observed 2026-08-16T12:04:16.917921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.262836Z digest=sha256:322bbe7c053e5a5fa02a7881bbb4a6ff73ff9d979dc62c60cffe07a636f0083d

Observation f8e902bd-85f4-4be0-bd46-dd2b4cbb0813 · outbound

This paper cites Appearance based deep domain adaptation for the classification of aerial images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Appearance based deep domain adaptation for the classification of aerial images,

Reference 50

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source=pdf_text observed=2026-08-16T12:04:16.267392Z digest=sha256:b38e5ab53527acf2791daae22921f9e1083b04147e1e4c4157f6785b71ac4944

Observation e3fdcc5b-c135-4686-be5f-6eb5cc8600b8 · outbound

This paper cites DSDANet: Deep Siamese Domain Adaptation Convolutional Neural Network for Cross-domain Change Detection.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection DSDANet: Deep Siamese Domain Adaptation Convolutional Neural Network for Cross-domain Change Detection

Reference 51

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.272217Z digest=sha256:c96939822c35923dd9860d84ee7944e5a9b40b9196372956d2943b1c537b4650

Observation e654e8e1-59a6-4631-b838-0f013e312d7f · outbound

This paper cites Domain adaptation for convolutional neural networks-based remote sensing scene classification,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Domain adaptation for convolutional neural networks-based remote sensing scene classification,

Reference 52

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.279617Z digest=sha256:ff302c943dfbc3e0cb589c7032a8eef6e6d1a72619c6fd397c30b9f79c4d8be8

Observation 0397e20b-36bc-4365-bf73-21e5262dc88a · outbound

This paper cites Domain adaptation using representation learning for the classification of remote sensing images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Domain adaptation using representation learning for the classification of remote sensing images,

Reference 53

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raw_fallback, observed 2026-08-16T12:04:16.845162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.285761Z digest=sha256:67d1c4be2c31bf83e1c4c2d800ed0a5b0b1b25140b334bffdc8455cbef500f0e

Observation 6759ff30-d38b-49b2-9bcf-db1b5fbc59bb · outbound

This paper cites Hiera: A hierarchi- cal vision transformer without the bells-and-whistles,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Hiera: A hierarchi- cal vision transformer without the bells-and-whistles,

Reference 54

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source=pdf_text observed=2026-08-16T12:04:16.293048Z digest=sha256:0be55e37cfe1ab805b337e1eee299c5409fb06b7c3ac0bccf59241c7a2c9c006

Observation 9d9c1be6-42c6-40d6-8b92-d5abbda20aaf · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Masked au- toencoders are scalable vision learners,

Reference 55

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raw_fallback, observed 2026-08-16T12:04:16.795954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.301482Z digest=sha256:37d0c03e88d170686c164c41503a4b38f13a9af67bee5322e2a4b5cb6aabf5e2

Observation e8b65ea5-aac5-48c1-96ba-d60a624c7f06 · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoen- coders,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Convnext v2: Co-designing and scaling convnets with masked autoen- coders,

Reference 56

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source=pdf_text observed=2026-08-16T12:04:16.307631Z digest=sha256:0cbc53e647a4da0efc68ba5e5db4ce5a355445dde94693e77d63fe3bdf34e6a9

Observation d6048620-f292-44c9-8fc9-bee8a1967846 · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Fixmatch: Simplifying semi- supervised learning with consistency and confidence,

Reference 57

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T12:04:16.314186Z digest=sha256:f9c6e1c8377f44091f58c5e0bac24edf8555c40af91cbe3e13429e2cdf9470fb

Observation 3ada09cc-2107-4410-873f-71c5c53449a2 · outbound

This paper cites Revisiting weak- to-strong consistency in semi-supervised semantic segmentation,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Revisiting weak- to-strong consistency in semi-supervised semantic segmentation,

Reference 58

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source=pdf_text observed=2026-08-16T12:04:16.321200Z digest=sha256:018e9e0d396d10412a0955b97d21f65480c9ebc7088ae4385f92acb941e1b17d

Observation 6bddcdca-9bdb-411b-8e60-4704a3352c17 · outbound

This paper cites A spatial-temporal attention-based method and a new dataset for remote sensing image change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection A spatial-temporal attention-based method and a new dataset for remote sensing image change detection,

Reference 59

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T12:04:16.328054Z digest=sha256:d62cf1c8fa15e5ebbdd61a8551865e4cd7b3a1d4a1c1ce9abad826561f3dc6b5

Observation 2c728e4b-8c03-4fe4-a93a-b96566532979 · outbound

This paper cites Decoupled Weight Decay Regularization.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Decoupled Weight Decay Regularization

Reference 60

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:16.333628Z digest=sha256:1351e6e110eb424b90c0eb0fa6129c4e93bee22442c04ef2ad7050c85da64450

Observation 59960126-ddeb-4065-bbaa-51ae274713c3 · outbound

This paper cites Sfda-cd: A source-free unsupervised domain adaptation for vhr image change detection,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Sfda-cd: A source-free unsupervised domain adaptation for vhr image change detection,

Reference 61

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raw_fallback, observed 2026-08-16T12:04:16.710743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.339314Z digest=sha256:733da65a2d3b0265cbbc9c3528653e6b2aa8b6e1830b04b8718b447458a95912

Observation a6016b8e-e98e-4e48-ae20-89d886360bf7 · outbound

This paper cites Multi-task learning using uncer- tainty to weigh losses for scene geometry and semantics,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Multi-task learning using uncer- tainty to weigh losses for scene geometry and semantics,

Reference 62

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:16.345605Z digest=sha256:52edd8b31af646b7b141cf9713f6efde74a5f8b35b1d627b0da9441b97b0c460

Observation a40845ee-fc3e-4304-9214-be42773b9166 · outbound

This paper cites Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images

Reference 63

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source=pdf_text observed=2026-08-16T12:04:16.353647Z digest=sha256:257167fc894672882b12ad90489aeee83db0543d6dd205b8bee30b5af06f370d

Observation 048cb6a7-29ff-4f37-8c6c-0bdd9c1a64d9 · outbound

This paper cites C2f-semicd: A coarse- to-fine semi-supervised change detection method based on consistency regularization in high-resolution remote sensing images,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection C2f-semicd: A coarse- to-fine semi-supervised change detection method based on consistency regularization in high-resolution remote sensing images,

Reference 64

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raw_fallback, observed 2026-08-16T12:04:16.657638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T12:04:16.360292Z digest=sha256:afc632e6dea7d95ddb62922634e289a64aa739ac21c19f7770987342d36333fc

Observation b5e49a53-f72e-45aa-a97d-c64054b4a2d8 · outbound

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

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 65

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:16.366432Z digest=sha256:c06953beef7daa8c96b0e5f46695a311140a7ddc5943493555f9acc4494e4005

Observation 15c7053e-a026-4f15-ae59-d3c9047e8936 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 66

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:16.373013Z digest=sha256:6e670470fd5e504c24352b70bd9f59c016f1bc6d11f3d7b5e10dad165234d465

Observation a30f4699-b1ea-482e-97c9-fad0a739220a · outbound

This paper cites Window Attention is Bugged: How not to Interpolate Position Embeddings.

DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection Window Attention is Bugged: How not to Interpolate Position Embeddings

Reference 67

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:16.380424Z digest=sha256:9325ca5f958d49de0f845a3bdc13d2c15444ba56060b610a852a06d13029f07a

Pith citing papers

No inbound Pith citation observations are available.