Paper Citation Record · LEDGER

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis

As of 9 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 1 inbound Pith citation observation for arXiv:2508.14509.

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

pith.paper-citation-record.v1
2508.14509 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:33:19.253414Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:48:36.048766Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:48:42.659276Z

Reference resolution

9 of 9 outbound references displayed

verified exact0
verified fuzzy7
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bcca385c-e07c-4642-844f-85d477ffa784 · outbound

This paper cites Deep semantic segmentation and skin disease classification from dermoscopic images based on a modernized deep learning network with multi-feature extraction[J].

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis Deep semantic segmentation and skin disease classification from dermoscopic images based on a modernized deep learning network with multi-feature extraction[J]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:20.699971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 84113fa0-66a5-4646-a6be-d4153130aad3 · outbound

This paper cites An artificial intelligence model for the semantic segmentation of neoplasms on imagesoftheskin[J].BiomedicalEngineering,2024,58(1):36-39.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis An artificial intelligence model for the semantic segmentation of neoplasms on imagesoftheskin[J].BiomedicalEngineering,2024,58(1):36-39

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:20.530573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ee022d80-efcc-488a-8db3-e613a0d0e56e · outbound

This paper cites A modified deep semantic segmentationmodelforanalysisofwholeslideskinimages[J].Scientific Reports,2024,14(1):23489.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis A modified deep semantic segmentationmodelforanalysisofwholeslideskinimages[J].Scientific Reports,2024,14(1):23489

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:20.365727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation af9179b0-4566-4509-bc87-c166affc6bff · outbound

This paper cites Semantic segmentation in skin surface microscopicimageswithartifactsremoval[J].ComputersinBiologyand Medicine,2024,180:108975.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis Semantic segmentation in skin surface microscopicimageswithartifactsremoval[J].ComputersinBiologyand Medicine,2024,180:108975

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:20.215396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d061f866-6235-4261-b74d-885fcabb082b · outbound

This paper cites Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example,.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:20.047058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3268543e-bc58-4f06-9de8-1ae5237987b3 · outbound

This paper cites Improved Skin Disease Classification By Segmentation and Feature Mapping using Deep Learning[C]//2024 4th Asian Conference on Innovation in Technology (ASIANCON).

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis Improved Skin Disease Classification By Segmentation and Feature Mapping using Deep Learning[C]//2024 4th Asian Conference on Innovation in Technology (ASIANCON)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:19.947868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fc83a677-3b08-4291-82aa-2ae76f38eb34 · outbound

This paper cites an unresolved cited work.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-05T18:33:19.719071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fa5dc3aa-aef6-40a6-b3e1-a585bd079597 · outbound

This paper cites Singapore: Springer Nature Singapore, 2024: 372-385.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis Singapore: Springer Nature Singapore, 2024: 372-385

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:33:19.547240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c61b662-73ef-4d24-abe5-2d30e667316a · outbound

This paper cites SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model.

Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T18:33:19.253414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation add18645-0401-49dc-942d-6ff4e64dedd2 · inbound

Topology-Aware Graph Reinforcement Learning for Dynamic Routing in Cloud Networks cites this paper.

Topology-Aware Graph Reinforcement Learning for Dynamic Routing in Cloud Networks Deep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:48:42.815733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.