Paper Citation Record · LEDGER

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation

As of 11 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2507.14790.

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

pith.paper-citation-record.v1
2507.14790 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:50:27.288473Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

verified exact0
verified fuzzy23
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dbb979c7-adec-427c-847c-5c68e4ae6827 · outbound

This paper cites Deformation models for image recognition[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Deformation models for image recognition[J]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:30.016392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 376ff2bb-38c1-4347-9be5-81a428736c50 · outbound

This paper cites Object detection with deep learning: A review[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Object detection with deep learning: A review[J]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.993967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 49ef3044-3182-4b79-803f-4fceb5f23690 · outbound

This paper cites Review the state-of-the-art technologies of semantic segmentation based on deep learning[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Review the state-of-the-art technologies of semantic segmentation based on deep learning[J]

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.976566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation da79ce1f-6af2-49e6-a9e9-6538038625d4 · outbound

This paper cites Imagenet classification with deep convolutional neural networks[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Imagenet classification with deep convolutional neural networks[J]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.955876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f5ade0b3-d51c-44f0-b8c3-1071526743b5 · outbound

This paper cites Going deeper with convolutions[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Going deeper with convolutions[C]//Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.925482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c138623a-bc05-4d21-905b-6e2ae6a1e8e6 · outbound

This paper cites Deep residual learning for image recognition[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Deep residual learning for image recognition[C]//Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T15:50:24.868829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd20d09d-c4da-431f-92dc-bd72c3ec09b6 · outbound

This paper cites an unresolved cited work.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:50:29.885015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b0b7d69c-a671-43b4-89d0-fec753e98538 · outbound

This paper cites LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation[J]

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.862695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dfdbd677-b47e-48e1-a2ea-8f66c8a49f02 · outbound

This paper cites Contextual ensemble network for semantic segmentation[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Contextual ensemble network for semantic segmentation[J]

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.813313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5c29daba-8944-4b33-afcf-1cde1f4b117e · outbound

This paper cites Linknet: Exploiting encoder representations for efficient semantic segmentation[C]//2017 IEEE visual communications and image processing (VCIP).

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Linknet: Exploiting encoder representations for efficient semantic segmentation[C]//2017 IEEE visual communications and image processing (VCIP)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.780682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e6a9d8eb-8c62-4f96-836e-6c36b7aedb12 · outbound

This paper cites Refinenet: Multi-path refinement networks for high-resolution semantic segmentation[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Refinenet: Multi-path refinement networks for high-resolution semantic segmentation[C]//Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.757971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 32922fc2-83af-40eb-b9b6-cf7bccb41696 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation[C]//Proceedings of the European conference on computer vision (ECCV).

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Encoder-decoder with atrous separable convolution for semantic image segmentation[C]//Proceedings of the European conference on computer vision (ECCV)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.729223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5046fe4e-e7a3-4990-b5fc-2373e1c03c4d · outbound

This paper cites Pyramid scene parsing network[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Pyramid scene parsing network[C]//Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.698595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e00d2de9-b78e-40cb-bb10-0d621ccc913f · outbound

This paper cites Progressive global perception and local polishing network for lung infection segmentation of COVID- 19 CT images[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Progressive global perception and local polishing network for lung infection segmentation of COVID- 19 CT images[J]

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.669903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2045ec5c-7a6c-4e7e-bd33-d2b7a01fb236 · outbound

This paper cites Deep high-resolution representation learning for visual recognition[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Deep high-resolution representation learning for visual recognition[J]

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.644560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e0d0bac5-73ed-41dd-8553-9e6b715ecdb1 · outbound

This paper cites Icnet for real-time semantic segmentation on high-resolution images[C]//Proceedings of the European conference on computer vision (ECCV).

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Icnet for real-time semantic segmentation on high-resolution images[C]//Proceedings of the European conference on computer vision (ECCV)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.609793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f6ed97f3-9133-4463-b08d-0664bf4f5148 · outbound

This paper cites DiSegNet: A deep dilated convolutional encoder-decoder architecture for lymph node segmentation on PET/CT images[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation DiSegNet: A deep dilated convolutional encoder-decoder architecture for lymph node segmentation on PET/CT images[J]

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.573944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 11502aad-0f65-4100-9299-5d986fde3401 · outbound

This paper cites Multi-modal unsupervised domain adaptation for semantic image segmentation[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Multi-modal unsupervised domain adaptation for semantic image segmentation[J]

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.538942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 289e77b7-7d03-47d4-b5a2-0111ff7b191c · outbound

This paper cites CANet: Co-attention network for RGB-D semantic segmentation[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation CANet: Co-attention network for RGB-D semantic segmentation[J]

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.507297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 97047b12-d112-4ef4-a76b-48eb88182c61 · outbound

This paper cites Rgbd-net: Predicting color and depth images for novel views synthesis[C]//2021 International Conference on 3D Vision (3DV).

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Rgbd-net: Predicting color and depth images for novel views synthesis[C]//2021 International Conference on 3D Vision (3DV)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.326435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f11be8b5-6ac7-437e-813b-e85ee60273dd · outbound

This paper cites Semantic segmentation with boundary neural fields[C]//Proceedings of the IEEE conference on computer vision and pattern recognition.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Semantic segmentation with boundary neural fields[C]//Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:29.073213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9931b106-c31b-439f-904a-bfcbfa7f9359 · outbound

This paper cites Edge detection techniques-an overview[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Edge detection techniques-an overview[J]

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:28.729840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 662507cb-1aec-49b9-bbc4-4b2853ccdef3 · outbound

This paper cites A color image segmentation method as used in the study of ancient monument decay[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation A color image segmentation method as used in the study of ancient monument decay[J]

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:28.432860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0ea4aa2e-ae89-449d-b06a-af864ef5c321 · outbound

This paper cites Terahertz plasmonic high pass filter[J].

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Terahertz plasmonic high pass filter[J]

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:28.237860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a629a569-9d24-4e68-bf5e-67428d751a1f · outbound

This paper cites an unresolved cited work.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:50:27.980426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2b746cdf-135b-4814-9e48-2bda07099adb · outbound

This paper cites Fast-SCNN: Fast Semantic Segmentation Network.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Fast-SCNN: Fast Semantic Segmentation Network

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T15:50:27.106430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac0baac1-a42e-400f-ab87-a404603558e6 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:50:27.190072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a0de567-150e-48cd-a4a5-d9b951b6b226 · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation[C]//European conference on computer vision.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation Swin-unet: Unet-like pure transformer for medical image segmentation[C]//European conference on computer vision

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:50:27.532793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fd9466ff-73cd-46ef-9555-40f53274a625 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

A Novel Downsampling Strategy Based on Information Complementarity for Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:50:27.288473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.