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Paper Citation Record · LEDGER

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification

As of 20 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.07518.

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

pith.paper-citation-record.v1
2607.07518 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T08:22:10.120572Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fcfc5888-e7ad-43db-912d-64a4f9cb1903 · outbound

This paper cites European Radiology31(5), 2706– 2715 (2021).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification European Radiology31(5), 2706– 2715 (2021)

Reference 1

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This paper cites In: International Conference on Medi- cal Image Computing and Computer-Assisted Intervention.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Conference on Medi- cal Image Computing and Computer-Assisted Intervention

Reference 2

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Observation 4006a73b-9c5a-408d-876d-4d5d496b2c34 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 3

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Observation 50a4ecd3-7dcb-429b-9dc6-76b8fd3f9a3e · outbound

This paper cites Medical image analysis12(1), 26–41 (2008).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Medical image analysis12(1), 26–41 (2008)

Reference 4

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Observation 7c4f42df-1d3b-464d-87f0-b536059e3b8d · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Neural Machine Translation by Jointly Learning to Align and Translate

Reference 5

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Observation 7e02927b-9bae-4bc7-88f2-90ae8b2bce90 · outbound

This paper cites IEEE transactions on medical imaging38(8), 1788–1800 (2019).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification IEEE transactions on medical imaging38(8), 1788–1800 (2019)

Reference 6

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Observation d9b236bc-d143-4d5d-b2f3-e6d2b2be7b27 · outbound

This paper cites International journal of computer vision61, 139–157 (2005).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification International journal of computer vision61, 139–157 (2005)

Reference 7

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Observation c0f8aae7-ea4f-4823-8d39-bb4278fe672a · outbound

This paper cites European Radiology 34(9), 5691–5704 (2024).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification European Radiology 34(9), 5691–5704 (2024)

Reference 8

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Observation 4cc5e9ba-57e5-4dca-8ed7-5175215d2b10 · outbound

This paper cites In: Proceedings of the AAAI conference on artificial intelligence.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: Proceedings of the AAAI conference on artificial intelligence

Reference 9

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Observation 734655e9-e9e0-4cf6-8dcb-5ea4391b97d3 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 10

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Observation a37da34d-f426-4460-8353-973f1ec39e92 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

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Observation 1335c1e9-f67d-4aad-abf3-9c512722e5ef · outbound

This paper cites European Heart Journal-Cardiovascular Imaging 19(7), 816–823 (2018).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification European Heart Journal-Cardiovascular Imaging 19(7), 816–823 (2018)

Reference 12

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Observation e32fdeb5-844c-4dcf-9734-75c2d7a28a72 · outbound

This paper cites BMC Cardiovascular Disorders23(1), 162 (2023).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification BMC Cardiovascular Disorders23(1), 162 (2023)

Reference 13

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Observation 3b0850f2-36a3-4550-940a-59e9db415c35 · outbound

This paper cites an unresolved cited work.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Unresolved cited work

Reference 14

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Observation 9fad4f7c-b476-479f-8699-3f1c8b6a1a86 · outbound

This paper cites Invariant Shape Representation Learning For Image Classification.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Invariant Shape Representation Learning For Image Classification

Reference 15

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This paper cites In: International Conference on Information Processing in Med- ical Imaging.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Conference on Information Processing in Med- ical Imaging

Reference 16

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Observation 7484ca8b-f60c-43f3-9292-322b163c03ff · outbound

This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 17

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Observation 9fae296b-bb79-4caf-b473-ea8ca9dd1d33 · outbound

This paper cites Journal of Magnetic Resonance Imaging61(4), 1635–1647 (2025).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Journal of Magnetic Resonance Imaging61(4), 1635–1647 (2025)

Reference 18

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Observation 76416303-e1d7-4a63-8908-13a5a765acfe · outbound

This paper cites In: International Workshop on Shape in Medical Imaging.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Workshop on Shape in Medical Imaging

Reference 19

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Observation 44f86cfc-5c6c-41bd-852b-f3680ea8c461 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Adam: A Method for Stochastic Optimization

Reference 20

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Observation 07f34002-778b-4eab-8752-ef0c315d0c36 · outbound

This paper cites IEEE Journal of Biomedical and Health Informatics26(7), 3209–3217 (2022).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification IEEE Journal of Biomedical and Health Informatics26(7), 3209–3217 (2022)

Reference 21

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Observation ca6baf4d-280e-408f-aa19-4aa916567cd7 · outbound

This paper cites Medical Image Analysis83, 102682 (2023).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Medical Image Analysis83, 102682 (2023)

Reference 22

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This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 23

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Observation 5e40f9de-26c1-4e22-ac25-7916d7e8f39e · outbound

This paper cites Advances in neural information pro- cessing systems30(2017).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Advances in neural information pro- cessing systems30(2017)

Reference 24

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This paper cites The Conference on Neural Information Processing Systems (2022).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification The Conference on Neural Information Processing Systems (2022)

Reference 25

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Observation 34cf898c-b5df-4786-bfde-ee0999f7401b · outbound

This paper cites Cardiovascular Imaging15(3), 413–427 (2022).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Cardiovascular Imaging15(3), 413–427 (2022)

Reference 26

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This paper cites Medical image analysis 1(1), 35–51 (1996).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Medical image analysis 1(1), 35–51 (1996)

Reference 27

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This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d67362d2-ab56-4d6c-b716-a861948a72c1 · outbound

This paper cites International Journal of Computer Assisted Radiology and Surgery19(2), 355–365 (2024).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification International Journal of Computer Assisted Radiology and Surgery19(2), 355–365 (2024)

Reference 29

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verified fuzzy
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Source-reported events for the cited work

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Observation 2f10dcec-b4d6-451a-ad98-65561390e595 · outbound

This paper cites In: International Workshop on Shape in Medical Imaging.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: International Workshop on Shape in Medical Imaging

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2cfed0bf-9f1f-4dbe-b408-05dabc5023a5 · outbound

This paper cites In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification In: 2024 IEEE International Symposium on Biomedical Imaging (ISBI)

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 89bf0d06-87c7-47fe-b55c-c7f47ae6fed6 · outbound

This paper cites Medical image analysis56, 80–95 (2019).

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Medical image analysis56, 80–95 (2019)

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

No inbound Pith citation observations are available.