Paper Citation Record · LEDGER

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images

As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:1908.11080.

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

pith.paper-citation-record.v1
1908.11080 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:33:01.207918Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

32 of 32 outbound references displayed

verified exact1
verified fuzzy21
unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 35af4643-5714-45d1-b3d5-5e0be7af02cf · outbound

This paper cites Support vector machines in remote sensing: A review.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Support vector machines in remote sensing: A review

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.709233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b0fab5e2-e17e-4a69-b252-6c7d6aeba9f3 · outbound

This paper cites Neural network classification of remote - sensing data.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Neural network classification of remote - sensing data

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.694932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f2f8d4ec-e008-4ef1-b369-e430cb05a7e4 · outbound

This paper cites Random forest classifier for remote sensing classification.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Random forest classifier for remote sensing classification

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.680107Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5acac08e-af34-48ee-94a2-a12c0d789ff6 · outbound

This paper cites Object - b ased image analysis for remote sensing.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Object - b ased image analysis for remote sensing

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.666184Z

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Observation b43aaaf2-35bf-45f0-aa6a-556b427dff48 · outbound

This paper cites Object Recognition from Local gre Scale - Invariant Features.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Object Recognition from Local gre Scale - Invariant Features

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.652136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation caf231fd-8756-4f27-9076-f981795ce681 · outbound

This paper cites Histog rams of Oriented Gradients for Human Detection.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Histog rams of Oriented Gradients for Human Detection

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.637869Z

Source-reported events for the cited work

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Observation 0b209c93-3dcf-4d8d-8b62-010911efdfd1 · outbound

This paper cites Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 7

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Source-reported events for the cited work

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Observation ee250ca5-05c5-4c3c-8b38-60b31808e01f · outbound

This paper cites Holistically - Nested Edge Detection[J].

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Holistically - Nested Edge Detection[J]

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.622636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 17d3e570-273d-40f1-93d2-6e9a6eb09d41 · outbound

This paper cites an unresolved cited work.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:33:01.608621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3e057174-cce6-44e1-9f92-40004c7bb9a4 · outbound

This paper cites , Ferretti , A.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images , Ferretti , A

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.595014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 80ebf89b-0ded-4596-ba91-221e850e1055 · outbound

This paper cites M onitoring abandoned dreg fields of high - speed railway construction with UAV remote sensing technology.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images M onitoring abandoned dreg fields of high - speed railway construction with UAV remote sensing technology

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.580815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a08532ba-939d-4a97-a855-1b0575c854c5 · outbound

This paper cites an unresolved cited work.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:33:01.565931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a04182c9-9223-484f-bb6d-7d9a4b761557 · outbound

This paper cites Automated recognition of railroad infrastructure in r ural areas from lidar data.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Automated recognition of railroad infrastructure in r ural areas from lidar data

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.551860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1cf649f8-b27c-403d-bfb3-1f4b97662bae · outbound

This paper cites Fully convolutional networks for semantic segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Fully convolutional networks for semantic segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.536557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a3a40ac1-73c1-41c5-a28f-8811e5daad5e · outbound

This paper cites The pascal visual object classes challenge: A retrospective.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images The pascal visual object classes challenge: A retrospective

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.521951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 273a34d1-38f3-46e6-ac2e-5e99ff540f32 · outbound

This paper cites - Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollar, P.; Zitnick, C.L.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images - Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollar, P.; Zitnick, C.L

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.507626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7000da12-d5d0-4d88-aafe-26560abf173c · outbound

This paper cites SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Reference 17

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Source-reported events for the cited work

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Observation 19b3473c-283a-45f9-ba94-98a3aa5f2aaa · outbound

This paper cites U - Net: Convolutional Networks for Biomedical Image Segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images U - Net: Convolutional Networks for Biomedical Image Segmentation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.493107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bcce281e-bec0-4f02-acc6-1d93a0caeb49 · outbound

This paper cites RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T10:33:01.146944Z

Source-reported events for the cited work

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Observation ce8588fa-de8e-4e5b-b187-8b15ffb82bdc · outbound

This paper cites LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T10:33:01.152245Z

Source-reported events for the cited work

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Observation ad494d6d-3115-4814-9704-c308ebfd0776 · outbound

This paper cites Pyramid Scene Parsing Network.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Pyramid Scene Parsing Network

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T10:33:01.157253Z

Source-reported events for the cited work

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Observation 66585673-5957-49ce-bb2a-aa545e5af8f1 · outbound

This paper cites Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T10:33:01.162215Z

Source-reported events for the cited work

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Observation 69f695d3-de6a-4dba-bbff-230c697714ed · outbound

This paper cites DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T10:33:01.167152Z

Source-reported events for the cited work

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Observation b3549869-5971-475f-aa22-718bd02b4db7 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T10:33:01.171810Z

Source-reported events for the cited work

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Observation 732f7b98-f7e3-45b0-a40d-d3565286b04f · outbound

This paper cites Dense semantic labeling of sub - decimeter resolution images with convolutional neu ral networks.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Dense semantic labeling of sub - decimeter resolution images with convolutional neu ral networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.478788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 57ead6b2-55dc-4952-b13b-06703b83aa10 · outbound

This paper cites Hourglass - ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Hourglass - ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.463130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0f6fbf53-2c6e-43ec-9235-a91cd47d9660 · outbound

This paper cites High-Resolution Semantic Labeling with Convolutional Neural Networks.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images High-Resolution Semantic Labeling with Convolutional Neural Networks

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:33:01.250002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 66c8b034-445c-4ca9-be18-6747f01fc734 · outbound

This paper cites Building Footprint Extraction from Hig h - Resolution Images via Spatial Residual Inception Convolutional Neural Network.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Building Footprint Extraction from Hig h - Resolution Images via Spatial Residual Inception Convolutional Neural Network

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.447053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f723fc93-0339-43ae-a811-4019c706042b · outbound

This paper cites Classification with an edge: Improving semantic image segmentation w ith boundary detection.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Classification with an edge: Improving semantic image segmentation w ith boundary detection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.432232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 173734bc-0405-4c81-9f4e-0d5c6215def9 · outbound

This paper cites Pixel - Wise Classification Method for High Resolution Remote Sensing Imagery Usi ng Deep Neural Networks.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Pixel - Wise Classification Method for High Resolution Remote Sensing Imagery Usi ng Deep Neural Networks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.417047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5dc806e-12ae-432a-9cff-dfc92f7226fe · outbound

This paper cites A Y - Net deep learning method for road seg mentation using high - resolution visible remote sensing images.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images A Y - Net deep learning method for road seg mentation using high - resolution visible remote sensing images

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.402109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5bb5fd02-5e00-416c-bd2b-6bd13b1e8020 · outbound

This paper cites Very Deep Convoluti onal Networks for Large - Scale Image Recognition.

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images Very Deep Convoluti onal Networks for Large - Scale Image Recognition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.386796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.