Paper Citation Record · LEDGER

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions

As of 21 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2412.20007.

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

pith.paper-citation-record.v1
2412.20007 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:44:41.426881Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

20 of 20 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 733b8ca2-61c4-49e9-8769-227c47729fbc · outbound

This paper cites Skin cancer facts page,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Skin cancer facts page,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.769918Z

Source-reported events for the cited work

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Observation 83718d8c-b213-4642-8d4a-b261357fa69b · outbound

This paper cites Skin cancer facts page,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Skin cancer facts page,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.752724Z

Source-reported events for the cited work

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Observation 00cff760-4164-400e-aba6-5124cce0c5e9 · outbound

This paper cites Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.736599Z

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Observation f0e2dfa1-3c53-4d7c-989a-bbb9f1a4cbf6 · outbound

This paper cites Current applications and future impact of machine learning in radiology,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Current applications and future impact of machine learning in radiology,

Reference 4

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Observation df158a08-cfcd-431f-b900-d668ae0fa653 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Dropout as a bayesian approximation: Representing model uncertainty in deep learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.704037Z

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Observation 5c80b00a-daaa-424a-8d08-20959de83693 · outbound

This paper cites Bayesian neural networks,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Bayesian neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.688334Z

Source-reported events for the cited work

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Observation d6892960-e80d-43e8-b7fa-d97004868da5 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,

Reference 7

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Source-reported events for the cited work

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Observation 844c779b-a119-49ce-bbec-d1ff95d358d5 · outbound

This paper cites Bayesian neural networks for uncertainty estimation of imaging biomarkers,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Bayesian neural networks for uncertainty estimation of imaging biomarkers,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.662018Z

Source-reported events for the cited work

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Observation 30aee9c5-92bd-431c-a40a-5946dbb9bc9c · outbound

This paper cites An exploration of un- certainty information for segmentation quality assessment,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions An exploration of un- certainty information for segmentation quality assessment,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.646249Z

Source-reported events for the cited work

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Observation 2f304a55-e0a0-4719-a3a9-beec4e588c2d · outbound

This paper cites Accuracy, uncertainty, and adaptability of automatic myocardial asl segmentation using deep cnn,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Accuracy, uncertainty, and adaptability of automatic myocardial asl segmentation using deep cnn,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.629919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 946a2431-1a19-4373-81d8-98331bdf04e9 · outbound

This paper cites Quantifying uncer- tainty of deep neural networks in skin lesion classification,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Quantifying uncer- tainty of deep neural networks in skin lesion classification,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.614798Z

Source-reported events for the cited work

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Observation 636bffbf-67d2-4919-a06d-38776d1fbc7d · outbound

This paper cites Un- certainty estimation in deep neural networks for dermoscopic image classification,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Un- certainty estimation in deep neural networks for dermoscopic image classification,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.599476Z

Source-reported events for the cited work

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Observation 804badb2-8c3f-4fb4-ab2f-1a10fb693fa8 · outbound

This paper cites Multi- class skin cancer classification architecture based on deep convolutional neural network,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Multi- class skin cancer classification architecture based on deep convolutional neural network,

Reference 13

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Observation f4986990-bd96-4f88-ac89-e2d1febc3f46 · outbound

This paper cites Melanoma segmentation using deep learning with test-time augmenta- tions and conditional random fields,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Melanoma segmentation using deep learning with test-time augmenta- tions and conditional random fields,

Reference 14

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Observation a27d44bc-61f0-47ad-9476-ceb76b8380e8 · outbound

This paper cites Skin lesion seg- mentation using deep learning for images acquired from smartphones,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Skin lesion seg- mentation using deep learning for images acquired from smartphones,

Reference 15

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Observation df9e80da-8264-4f93-b6e6-0ddbc67de253 · outbound

This paper cites Melanoma segmentation: A framework of im- proved densenet77 and unet convolutional neural network,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Melanoma segmentation: A framework of im- proved densenet77 and unet convolutional neural network,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.531954Z

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Observation 94939e87-d88a-45d4-99b5-d864d5eec0dc · outbound

This paper cites ISIC Archive homepage,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions ISIC Archive homepage,

Reference 17

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Source-reported events for the cited work

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Observation 09025622-c807-4cfd-96a2-d15b6025a6b8 · outbound

This paper cites BCN20000: Dermoscopic Lesions in the Wild.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions BCN20000: Dermoscopic Lesions in the Wild

Reference 18

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This paper cites A deep-learning toolkit for visualization and interpretation of segmented medical images,.

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions A deep-learning toolkit for visualization and interpretation of segmented medical images,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:44:41.499864Z

Source-reported events for the cited work

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Observation e55a8115-3bcc-475d-a4e7-c12402a8a48f · outbound

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

Uncertainty Quantified Deep Learning and Regression Analysis Framework for Image Segmentation of Skin Cancer Lesions Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T23:44:41.426881Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.