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Paper Citation Record · LEDGER

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations

As of 16 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:1908.08223.

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

pith.paper-citation-record.v1
1908.08223 v3

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:47:34.510935Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

29 of 29 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 89958e28-8587-4e38-a597-3fb95f8cd282 · outbound

This paper cites Deepglobe 2018: A challeng e to parse the earth through satellite images,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Deepglobe 2018: A challeng e to parse the earth through satellite images,

Reference 1

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Observation 55147356-5989-4f7c-9352-326698d9d399 · outbound

This paper cites A computational approach to edge detection,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations A computational approach to edge detection,

Reference 2

Resolution
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Observation e7e981d8-d460-43ee-8405-9e93137b4129 · outbound

This paper cites Use of the hough transformation to detect lines and curves in pictures.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Use of the hough transformation to detect lines and curves in pictures

Reference 3

Resolution
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Observation 5c48cd7f-e6de-49ce-8058-1323b815a9e5 · outbound

This paper cites Detection of linear features in sar images: Application to road network extraction,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Detection of linear features in sar images: Application to road network extraction,

Reference 4

Resolution
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Observation c2b012a2-30a5-4992-9be2-8e91d53d5256 · outbound

This paper cites Road extraction usi ng svm and image segmentation,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Road extraction usi ng svm and image segmentation,

Reference 5

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Source-reported events for the cited work

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Observation 7facf68a-3d63-4239-be87-ca7a12b4d086 · outbound

This paper cites Fully convolutio nal networks for semantic segmentation,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Fully convolutio nal networks for semantic segmentation,

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 890ccf12-7682-41fc-b184-6f052cd88b9e · outbound

This paper cites Road structure refined cnn for r oad extraction in aerial image,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Road structure refined cnn for r oad extraction in aerial image,

Reference 7

Resolution
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Source-reported events for the cited work

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Observation 9bf3556f-23fa-43d9-8a45-ace6dde280ca · outbound

This paper cites Pednet: A spa tio- temporal deep convolutional neural network for pedestrian segmenta- tion,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Pednet: A spa tio- temporal deep convolutional neural network for pedestrian segmenta- tion,

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 707209e1-cb2b-4ae5-abfc-4fb87d76b308 · outbound

This paper cites The one hundred layers tiramisu: Fully convolutional densenet s for semantic segmentation,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations The one hundred layers tiramisu: Fully convolutional densenet s for semantic segmentation,

Reference 9

Resolution
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Source-reported events for the cited work

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Observation a160809f-2e1e-47f3-ad16-a015101a2ab3 · outbound

This paper cites Road extraction by deep re sidual u- net,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Road extraction by deep re sidual u- net,

Reference 10

Resolution
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Source-reported events for the cited work

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Observation 41a8b9d5-cfa6-4288-89c5-5d0345112db2 · outbound

This paper cites Linknet: Exploiting encod er represen- tations for efficient semantic segmentation,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Linknet: Exploiting encod er represen- tations for efficient semantic segmentation,

Reference 11

Resolution
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Observation 63d65462-a7d1-4a86-b8ec-b47ed0c28147 · outbound

This paper cites D-linknet: Linknet with pre trained encoder and dilated convolution for high resolution satell ite imagery road extraction,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations D-linknet: Linknet with pre trained encoder and dilated convolution for high resolution satell ite imagery road extraction,

Reference 12

Resolution
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Observation 44e208b5-aaca-44ae-8703-0ee652fa2b05 · outbound

This paper cites Deepglobe 2018: A challen ge to parse the earth through satellite images,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Deepglobe 2018: A challen ge to parse the earth through satellite images,

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 8ab37365-c8ec-4a1b-a94f-dc54fd6aa35f · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 14

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Source-reported events for the cited work

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Observation 5c9332ea-2e57-4284-9be3-15aebebf50d2 · outbound

This paper cites Encoder- decoder with atrous separable convolution for semantic ima ge segmen- tation,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Encoder- decoder with atrous separable convolution for semantic ima ge segmen- tation,

Reference 15

Resolution
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Source-reported events for the cited work

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Observation a07ba973-641d-4655-b6d9-4f7638cc59fa · outbound

This paper cites Deformable Convolutional Networks.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Deformable Convolutional Networks

Reference 16

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Observation d1c2b2c9-5053-4218-9d2e-1d808ab9d86e · outbound

This paper cites Psanet: Point-wise spatial attention network for scene parsing,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Psanet: Point-wise spatial attention network for scene parsing,

Reference 17

Resolution
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Observation 90756257-7d0b-4ba0-9858-456592c6effa · outbound

This paper cites Parameter-Free Spatial Attention Network for Person Re-Identification.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Parameter-Free Spatial Attention Network for Person Re-Identification

Reference 18

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Source-reported events for the cited work

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This paper cites Visual sp atial attention network for relationship detection,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Visual sp atial attention network for relationship detection,

Reference 19

Resolution
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This paper cites Understanding t he effective receptive field in deep convolutional neural networks,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Understanding t he effective receptive field in deep convolutional neural networks,

Reference 20

Resolution
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Observation 89c09e0e-af9c-4a87-9598-ef234ebfd942 · outbound

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NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Non-local neu ral net- works,

Reference 21

Resolution
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Source-reported events for the cited work

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This paper cites Residual non -local attention networks for image restoration,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Residual non -local attention networks for image restoration,

Reference 22

Resolution
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Source-reported events for the cited work

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This paper cites Deep residual learni ng for image recognition,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Deep residual learni ng for image recognition,

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 5daa1987-9855-4a53-a375-fd86ae586fa4 · outbound

This paper cites Adam: A method for stochastic opt imization,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Adam: A method for stochastic opt imization,

Reference 24

Resolution
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Source-reported events for the cited work

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Observation c1c36b90-92ab-440b-8ee0-73758a3047cf · outbound

This paper cites A non-local algori thm for image denoising,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations A non-local algori thm for image denoising,

Reference 25

Resolution
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Source-reported events for the cited work

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Observation 52c829e1-a5f5-4dfa-ab4f-57f4f5c20fc8 · outbound

This paper cites Road detection w ith eosresunet and post vectorizing algorithm,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Road detection w ith eosresunet and post vectorizing algorithm,

Reference 26

Resolution
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Source-reported events for the cited work

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Observation bee7b080-a5c8-4611-a701-ba913765d908 · outbound

This paper cites Stacked u-nets with mu lti-output for road extraction,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Stacked u-nets with mu lti-output for road extraction,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation a43cf308-76c2-4ffe-a8c6-e01ffafceb0e · outbound

This paper cites Residual inception skip network for binary s egmentation,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Residual inception skip network for binary s egmentation,

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d84c0f51-8de0-435b-b8a7-bf36f88e97fe · outbound

This paper cites Fully convolution al networks for building and road extraction: Preliminary results,.

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations Fully convolution al networks for building and road extraction: Preliminary results,

Reference 29

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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