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Paper Citation Record · LEDGER

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation

As of 13 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2508.06517.

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

pith.paper-citation-record.v1
2508.06517 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:22:13.207462Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

59 of 59 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7372737d-b200-4e40-b3d4-44b63b87254e · outbound

This paper cites Worldwide variations in colorectal cancer.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Worldwide variations in colorectal cancer

Reference 1

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Observation f2f85a80-cdff-4ee8-88b1-a3aa000217fa · outbound

This paper cites Colorectal cancer.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Colorectal cancer

Reference 2

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Observation 1b47442c-7a4f-4597-8041-adac69052554 · outbound

This paper cites Colorectal cancer.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Colorectal cancer

Reference 3

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Observation 9dc1349c-70c2-46d8-8905-a4fb6a71e5fa · outbound

This paper cites Coinnet: A convolution-involution network with a novel statistical attention for automatic polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Coinnet: A convolution-involution network with a novel statistical attention for automatic polyp segmentation

Reference 4

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Source-reported events for the cited work

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Observation a5f6e689-3e96-4f1f-9674-27fae2748504 · outbound

This paper cites Know your orientation: A viewpoint-aware framework for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Know your orientation: A viewpoint-aware framework for polyp segmentation

Reference 5

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Observation 31a20c9c-d51a-4f5f-b060-f20fb4565460 · outbound

This paper cites Pranet: Parallel reverse attention network for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Pranet: Parallel reverse attention network for polyp segmentation

Reference 6

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Observation 849de3cd-257c-4c5a-8eb0-49cafe2f4472 · outbound

This paper cites Adaptive context selection for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Adaptive context selection for polyp segmentation

Reference 7

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Source-reported events for the cited work

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Observation 50363ade-dcb7-4c06-8463-236d134be2f6 · outbound

This paper cites Collaborative and adversarial learning of focused and dispersive representations for semi-supervised polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Collaborative and adversarial learning of focused and dispersive representations for semi-supervised polyp segmentation

Reference 8

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Source-reported events for the cited work

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Observation d2d9a925-2e64-4592-aa5a-02fc5a5928f4 · outbound

This paper cites Learning with local and global consistency.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Learning with local and global consistency

Reference 9

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Source-reported events for the cited work

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Observation 247e8225-9d69-4dad-9e8b-b3d42fe10e58 · outbound

This paper cites Fixmatch: Simplifying semi-supervised learning with consistency and confidence.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Fixmatch: Simplifying semi-supervised learning with consistency and confidence

Reference 10

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Observation 1388785e-c450-4339-b090-c37cc66a954b · outbound

This paper cites Revisiting weak-to-strong consistency in semi-supervised semantic segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Revisiting weak-to-strong consistency in semi-supervised semantic segmentation

Reference 11

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Observation ad9c6004-c1d7-41cf-bdda-b8301bdcbc3f · outbound

This paper cites Dual student: Breaking the limits of the teacher in semi-supervised learning.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Dual student: Breaking the limits of the teacher in semi-supervised learning

Reference 12

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Observation 9272f759-33da-43e6-b02e-92fe1980d136 · outbound

This paper cites Atso: Asynchronous teacher-student optimization for semi-supervised image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Atso: Asynchronous teacher-student optimization for semi-supervised image segmentation

Reference 13

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Observation 31c63218-c866-4434-8252-7c7aa7e1d64e · outbound

This paper cites Semi-supervised semantic segmentation with cross pseudo supervision.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Semi-supervised semantic segmentation with cross pseudo supervision

Reference 14

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Source-reported events for the cited work

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Observation 6026d494-5d60-4888-96b5-d37018b7234d · outbound

This paper cites Mutual consistency learning for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Mutual consistency learning for semi-supervised medical image segmentation

Reference 15

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Observation 1d266e39-b5f5-459b-a926-a9a13d4023aa · outbound

This paper cites Cuts: A deep learning and topological framework for multigranular unsupervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Cuts: A deep learning and topological framework for multigranular unsupervised medical image segmentation

Reference 16

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Observation 7e61c2a8-f235-490b-9400-d9d02662dc60 · outbound

This paper cites Ambiguity-selective consistency regularization for mean-teacher semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Ambiguity-selective consistency regularization for mean-teacher semi-supervised medical image segmentation

Reference 17

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Observation 3115c6d9-e618-4864-b767-fa2d70e4d782 · outbound

This paper cites Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency

Reference 18

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Observation c4ad376e-211c-409b-8ddf-575f2a65409a · outbound

This paper cites Inconsistency-aware uncertainty estimation for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Inconsistency-aware uncertainty estimation for semi-supervised medical image segmentation

Reference 19

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Observation b48bab16-3c14-40cb-9ace-d5957db2be84 · outbound

This paper cites Compete to win: Enhancing pseudo labels for barely-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Compete to win: Enhancing pseudo labels for barely-supervised medical image segmentation

Reference 20

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Observation e7f83fed-132d-4046-8d75-cd53f90106ba · outbound

This paper cites Pseudo-label guided contrastive learning for semi- supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Pseudo-label guided contrastive learning for semi- supervised medical image segmentation

Reference 21

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Source-reported events for the cited work

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Observation 7c35c895-1fb0-476c-b4b5-74010b846a88 · outbound

This paper cites Rcps: Rectified contrastive pseudo supervision for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Rcps: Rectified contrastive pseudo supervision for semi-supervised medical image segmentation

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 8e5a8cdd-954c-494d-95d2-ac27549f1aa4 · outbound

This paper cites Semi- supervised medical image segmentation using adversarial consistency learning and dynamic convolution network.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Semi- supervised medical image segmentation using adversarial consistency learning and dynamic convolution network

Reference 23

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Source-reported events for the cited work

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Observation 850099c4-d0ff-4eec-8724-227402f1a07b · outbound

This paper cites Semi-supervised medical image segmentation through dual-task consistency.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Semi-supervised medical image segmentation through dual-task consistency

Reference 24

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Source-reported events for the cited work

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Observation b896120a-2d31-462d-ac03-7b545ee424b9 · outbound

This paper cites Diffkillr: Killing and recreating diffeomorphisms for cell annotation in dense microscopy images.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Diffkillr: Killing and recreating diffeomorphisms for cell annotation in dense microscopy images

Reference 25

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Source-reported events for the cited work

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Observation 01747c6c-d4da-415b-803f-c64402d4e58a · outbound

This paper cites Rethinking copy-paste for consistency learning in medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Rethinking copy-paste for consistency learning in medical image segmentation

Reference 26

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Source-reported events for the cited work

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Observation 7ef1d2dc-17d7-4244-937f-2b559e49cdc4 · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Cutmix: Regularization strategy to train strong classifiers with localizable features

Reference 27

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Source-reported events for the cited work

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Observation 4c84854a-b66e-4084-85a7-95597e88873a · outbound

This paper cites Learn to threshold: Thresholdnet with confidence-guided manifold mixup for polyp segmentation.IEEE transactions on medical imaging, 40(4):1134–1146, 2020.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Learn to threshold: Thresholdnet with confidence-guided manifold mixup for polyp segmentation.IEEE transactions on medical imaging, 40(4):1134–1146, 2020

Reference 28

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Source-reported events for the cited work

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Observation 76388698-227d-4a80-85fe-1403c453683c · outbound

This paper cites Msrf-net: a multi-scale residual fusion network for biomedical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Msrf-net: a multi-scale residual fusion network for biomedical image segmentation

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f29040ce-b799-418b-afa5-e54f3ff4b5b4 · outbound

This paper cites Fuzzynet: A fuzzy attention module for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Fuzzynet: A fuzzy attention module for polyp segmentation

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation afc4e306-e3b9-454f-a8b0-9db3b49f2dad · outbound

This paper cites Cross- level feature aggregation network for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Cross- level feature aggregation network for polyp segmentation

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c7285a68-2544-4deb-9a10-93adc88171f6 · outbound

This paper cites Meganet: Multi-scale edge-guided attention network for weak boundary polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Meganet: Multi-scale edge-guided attention network for weak boundary polyp segmentation

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.137030Z digest=sha256:8ed08a75141561c7858c75c8019214a843543fec863c06e552c82ddd12bd498c

Observation 6d2e7bff-2f04-4a62-98b1-dcb1fa00101c · outbound

This paper cites Uacanet: Uncertainty augmented context attention for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Uacanet: Uncertainty augmented context attention for polyp segmentation

Reference 33

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raw_fallback, observed 2026-08-06T11:22:13.439708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.139663Z digest=sha256:4344cdcc6fd7bbdb755ff78d71ddb131ef2afd135e8ac342d2dc8b16d44e38e4

Observation ff05cf1f-a393-4b50-90f1-67812c236bf2 · outbound

This paper cites Shallow attention network for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Shallow attention network for polyp segmentation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.431999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.142295Z digest=sha256:6d8790a614adb44cc42a261ab7739394683214d6e73f7da411efda393c33d74c

Observation 28cb4658-fccf-4f94-af78-771147365e9d · outbound

This paper cites Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T11:22:13.144919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:22:13.144919Z digest=sha256:e12e72cd5a4f4bcafafa8f8e31553143e16a0788dd0e8c5bc7f08847fc98d9ec

Observation 6fcf5b77-13f9-48d3-ba61-c82c44ce4a1a · outbound

This paper cites Ctnet: Contrastive transformer network for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Ctnet: Contrastive transformer network for polyp segmentation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.424907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.148058Z digest=sha256:f5c6257e8ecd31aad76cc0b6b2025ecc97def8adba22f41c00e54dd4484aab7a

Observation 19fdb64b-3a1a-4a7c-a797-42cd2714179c · outbound

This paper cites Fcn-transformer feature fusion for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Fcn-transformer feature fusion for polyp segmentation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.417780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.150496Z digest=sha256:218164864a924cb71f9265c40d1842c132f256a73cf29f129fd5dc0df0a91f8d

Observation 8050f4a9-81f2-48ce-b244-58c5bf0672a9 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation mixup: Beyond Empirical Risk Minimization

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T11:22:13.153386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:22:13.153386Z digest=sha256:466fa3b65d4b55df72ae0c1c1430f7912c8d55e2e39757d8d37f9fc44e6d3797

Observation 37f2a6e0-011e-4372-97be-217c5de385ad · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Improved Regularization of Convolutional Neural Networks with Cutout

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T11:22:13.156289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:22:13.156289Z digest=sha256:222edc4b14a2b5f326422bbcd0f8af13cb122a08817a691a8e0fc57bb44a7032

Observation a7c6e18b-70b6-438d-974f-2261441f68af · outbound

This paper cites Bidirectional copy-paste for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Bidirectional copy-paste for semi-supervised medical image segmentation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.410633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.159463Z digest=sha256:535262432582dbe25126b8cde68127f77c993a6e30c262a95189edd189d8ebb1

Observation 3b74f9d6-48fe-4e9c-a51b-caba08d7caf6 · outbound

This paper cites AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T11:22:13.162458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:22:13.162458Z digest=sha256:d56d214ca642497f6789524b51ded873678edc6a8ac07e9e33afc550663419b0

Observation 952cfa54-3c5c-4475-b15e-59c1fce9beeb · outbound

This paper cites Dfm-x: Augmentation by leveraging prior knowledge of shortcut learning.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Dfm-x: Augmentation by leveraging prior knowledge of shortcut learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.403320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.165784Z digest=sha256:2d2d93efb5f2563cfa6ca40d4eb0bdaf40cc2b282a4ef7c8f0f83afc9165e96c

Observation 10615654-5512-41c1-89c2-20fa029f5cbb · outbound

This paper cites A fourier-based framework for domain generalization.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation A fourier-based framework for domain generalization

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.396059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.168373Z digest=sha256:a7e71c7fbffcf17b91155776c90188901d77f90283334545cd228642a9b35034

Observation 3d24dbc5-99f5-4402-ad86-9df36303131e · outbound

This paper cites Fsdr: Frequency space domain randomization for domain generalization.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Fsdr: Frequency space domain randomization for domain generalization

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.388425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.171023Z digest=sha256:c178bb3584cc9c8eefbbdb0b0652051bc1f34380775fd6d5fe4a850a2d20d85b

Observation 0defca38-2c1d-4db8-b7c1-49a1c4a57f6f · outbound

This paper cites Design of an image edge detection filter using the sobel operator.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Design of an image edge detection filter using the sobel operator

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.381176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.173464Z digest=sha256:06ca5c7ebe43779930bd1aea410d963ec95497110f51fa82563cac1820c9f7fe

Observation b3c6a2dd-69e7-48f3-8a4e-8ab2367dd4dd · outbound

This paper cites Combo loss: Handling input and output imbalance in multi-organ segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Combo loss: Handling input and output imbalance in multi-organ segmentation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.373543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.175904Z digest=sha256:7ebabd7806b7f174aa64d89aa19ecabb6c0253c7abeab604f556f1c93859f3af

Observation 179e68f5-c6a9-4bd9-b19b-c6d020ceaf96 · outbound

This paper cites Kvasir-seg: A segmented polyp dataset.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Kvasir-seg: A segmented polyp dataset

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.366044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.178143Z digest=sha256:5078bd38eef1099fe44393d4dda16c7867fc23594c737917134224c5ea80573c

Observation b8d406a6-5956-433a-affd-16e5a1878571 · outbound

This paper cites Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.358319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.180580Z digest=sha256:3679a2de72c275c0b1b8a7dee397720350f8778c5c115a26e5cf6bc9a5c9d689

Observation 638b8830-95dd-4c59-b6f6-f72cd71e0d6e · outbound

This paper cites Toward embedded detection of polyps in wce images for early diagnosis of colorectal cancer.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Toward embedded detection of polyps in wce images for early diagnosis of colorectal cancer

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.350770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.183099Z digest=sha256:bb58ef2a0af2a3ba3ec7428dcc163f3cb2c0cfaac916d6574e6d449605b0a27d

Observation 59ba60a5-92a5-4d96-9bf0-44a21470e43c · outbound

This paper cites Towards automatic polyp detection with a polyp appearance model.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Towards automatic polyp detection with a polyp appearance model

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.343195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.185562Z digest=sha256:33427e346f687f515f4f0d1d87f3bbbe3339d5a7e33c2bbd170035bd7217fd92

Observation 2c43fff4-1d97-4f0a-8ddb-5ab466b538ae · outbound

This paper cites Bkai-igh neopolyp.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Bkai-igh neopolyp

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.335647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.187932Z digest=sha256:e9a0223825b7edd54e1c1a6277061aef98ba91d8a6815cb2d3899712c9666afa

Observation 8a9629e3-d512-4c4a-b9fa-83f60fd95158 · outbound

This paper cites Dynamic spectrum-driven hierarchical learning network for polyp segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Dynamic spectrum-driven hierarchical learning network for polyp segmentation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.327704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.190484Z digest=sha256:87df285b09b3409859359bdbed9a1d066ba9f4652473a8ce7b3fbf0795772165

Observation fed67ff0-18c3-4952-845c-f88d3c400c99 · outbound

This paper cites Bilateral supervision network for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Bilateral supervision network for semi-supervised medical image segmentation

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.319852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.192932Z digest=sha256:ed6944ac155707daa52e162fde7e18e279eab9e0b1af2c0b379ea45c8611ff87

Observation 508301c5-9250-46bf-bfbd-9d2fa06385d5 · outbound

This paper cites Caussl: Causality- inspired semi-supervised learning for medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Caussl: Causality- inspired semi-supervised learning for medical image segmentation

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.311471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.195348Z digest=sha256:6e639567a7e8de0e4ee91d95ac7d959fdd79320540c07c06b3b1ec4e9fd48579

Observation deb2fd8b-1a61-48cf-932c-f75dce6f9e3f · outbound

This paper cites Adaptive bidirectional displacement for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Adaptive bidirectional displacement for semi-supervised medical image segmentation

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.301793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.197762Z digest=sha256:e2adaa283e0babf59455dd54134a5a17931d97c9b3ebb6924f392366e6d10b1c

Observation fbedb48f-7270-49ca-babc-9fcc451d8b55 · outbound

This paper cites Dycon: Dynamic uncertainty-aware consistency and contrastive learning for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Dycon: Dynamic uncertainty-aware consistency and contrastive learning for semi-supervised medical image segmentation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.293671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.200275Z digest=sha256:bb985e90d82d8809e50267ecb885f0ac5a5664104742ada33e96c8e85c3d1c98

Observation ca66cc65-9ed1-4197-bc92-526ce4412388 · outbound

This paper cites Background matters: A cross-view bidirectional modeling framework for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Background matters: A cross-view bidirectional modeling framework for semi-supervised medical image segmentation

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.285683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.202581Z digest=sha256:b9654f8aafa435408ed19f2b99c38802f431e18a366797d668d595e702b5109f

Observation 21a45222-1b19-4089-8807-27629ba60899 · outbound

This paper cites Pick: Predict and mask for semi-supervised medical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation Pick: Predict and mask for semi-supervised medical image segmentation

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.277341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.205161Z digest=sha256:cf376375cb92bcde5707824ab9bf68bc540e8aa3cf3974764c2856d9765d4ab1

Observation efb4a775-c4f4-48d5-8b38-516b21da54c7 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Frequency Prior Guided Matching: A Data Augmentation Approach for Generalizable Semi-Supervised Polyp Segmentation U-net: Convolutional networks for biomedical image segmentation

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:22:13.268781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T11:22:13.207462Z digest=sha256:42806677472cb8277484abe2cbdb8a5e8d684f1ca470351415f961e8d69cb6e3

Pith citing papers

No inbound Pith citation observations are available.