EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation | Paper Citation Record

Observation 31f5840e-3a03-42f3-8727-f54942336d49 · outbound

This paper cites Dmsps: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Dmsps: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.825766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c2db02ee-cd65-4c64-809a-f2f614a50ee1 · outbound

This paper cites Pa-seg: Learning from point annotations for 3d medical image segmentation using contextual regularization and cross knowledge distillation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Pa-seg: Learning from point annotations for 3d medical image segmentation using contextual regularization and cross knowledge distillation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.797358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a6b267fa-f575-4d61-aa0b-8d266ab6fb69 · outbound

This paper cites Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.772873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a8c0337-f0fd-4dcc-a1c5-1dbba5f87351 · outbound

This paper cites Weakly supervised brain lesion segmentation via attentional representation learn- ing,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Weakly supervised brain lesion segmentation via attentional representation learn- ing,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.736013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6c6bb3bf-776c-48e7-811b-8b074de4d25c · outbound

This paper cites Scribblesup: Scribble- supervised convolutional networks for semantic segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Scribblesup: Scribble- supervised convolutional networks for semantic segmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.694955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dd796216-194a-4bff-be8c-5a8fe6a4c89d · outbound

This paper cites Deepcut: Object segmentation from bounding box annotations using convolutional neural networks,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Deepcut: Object segmentation from bounding box annotations using convolutional neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.666805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac600eaa-6c9c-4ede-8c1c-9237f1d93c02 · outbound

This paper cites Inter extreme points geodesics for end-to-end weakly supervised image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Inter extreme points geodesics for end-to-end weakly supervised image segmentation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.649263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fce4ea2f-533c-4f48-a7ef-0ec5cdc4a8f2 · outbound

This paper cites Scribblevc: Scribble- supervised medical image segmentation with vision-class embedding,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Scribblevc: Scribble- supervised medical image segmentation with vision-class embedding,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.618429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b3094b86-ea10-4e58-a6c4-dccb7d533628 · outbound

This paper cites Blpseg: Balance the label preference in scribble-supervised semantic segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Blpseg: Balance the label preference in scribble-supervised semantic segmentation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.589247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fce3f9a6-b9b9-4a55-be52-b5ab2210658a · outbound

This paper cites Sparsely annotated semantic segmentation with adaptive gaussian mixtures,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Sparsely annotated semantic segmentation with adaptive gaussian mixtures,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.533932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac8888a1-d8b9-4089-b283-684f6a11626b · outbound

This paper cites an unresolved cited work.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:27:10.488984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9633b30e-ba39-48bb-9aff-e4508d16e895 · outbound

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

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Kvasir-seg: A segmented polyp dataset,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.449229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1074145-da76-497f-9a73-893f73821df9 · outbound

This paper cites Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.409679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 386e90fb-a6c9-405b-b50b-9c8ebb0d8d87 · outbound

This paper cites Learning deep features for discriminative localization,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Learning deep features for discriminative localization,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:08.883457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b91c8913-1f03-406d-bf98-a039b5e38515 · outbound

This paper cites Intra-class consistency and inter-class discrimination feature learning for automatic skin lesion classification,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Intra-class consistency and inter-class discrimination feature learning for automatic skin lesion classification,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.358135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b3aff420-564b-4c2b-9880-96189ad01b35 · outbound

This paper cites Weakly supervised instance segmentation using the bounding box tightness prior,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Weakly supervised instance segmentation using the bounding box tightness prior,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.323458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 18c140c8-2d7e-4b32-a8c0-8de86a77818a · outbound

This paper cites Learning to segment from scribbles using multi-scale adversarial attention gates,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Learning to segment from scribbles using multi-scale adversarial attention gates,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.293668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26bf7423-9aa1-42b2-a609-e9c8b5505006 · outbound

This paper cites Scribble-based hierarchical weakly supervised learning for brain tumor segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Scribble-based hierarchical weakly supervised learning for brain tumor segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.270030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4cd3498c-30a2-48d1-9163-f84c65f50d45 · outbound

This paper cites Cyclemix: A holistic strategy for medical image segmentation from scribble supervision,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Cyclemix: A holistic strategy for medical image segmentation from scribble supervision,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.244964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a3592b11-7510-4e8e-93e5-0ce607aabaf3 · outbound

This paper cites Simclr: A simple framework for contrastive learning of visual representations,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Simclr: A simple framework for contrastive learning of visual representations,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.217230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac0427b2-0b72-4292-9494-804abfb22259 · outbound

This paper cites A survey on contrastive self-supervised learning,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation A survey on contrastive self-supervised learning,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.106371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4ae6d56-4fd1-4ca1-97e5-97b003a41608 · outbound

This paper cites Rethinking semi-supervised medical image segmentation: A variance-reduction perspective,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Rethinking semi-supervised medical image segmentation: A variance-reduction perspective,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.174539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41a32b01-826f-411b-a72a-3e4359eec003 · outbound

This paper cites Exploring cross-image pixel contrast for semantic segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Exploring cross-image pixel contrast for semantic segmentation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.146748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5cf01a63-45cd-4e60-b918-bd0d260a1d8d · outbound

This paper cites Uncertainty-guided pixel contrastive learning for semi-supervised medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Uncertainty-guided pixel contrastive learning for semi-supervised medical image segmentation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.118267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9fd08684-58ba-47fb-9943-f034c42d9366 · outbound

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

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.137857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba6f55fd-3033-4212-8c7f-f1fc762d6b5f · outbound

This paper cites Encoder- decoder with atrous separable convolution for semantic image segmen- tation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Encoder- decoder with atrous separable convolution for semantic image segmen- tation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.067979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 43a3292d-cf03-45e2-b9db-3b5ee7a33427 · outbound

This paper cites Transunet: Rethinking the u-net architecture design for medical image segmentation through the lens of transformers,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Transunet: Rethinking the u-net architecture design for medical image segmentation through the lens of transformers,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.045123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ea5a382e-0ce2-478e-8801-c34ef835f7f5 · outbound

This paper cites Exploring feature representation learning for semi-supervised medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Exploring feature representation learning for semi-supervised medical image segmentation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:10.021285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48072a7c-64a9-4a8b-88ae-45b3d213541f · outbound

This paper cites Contrastive registra- tion for unsupervised medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Contrastive registra- tion for unsupervised medical image segmentation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.995584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a9f7b2d0-fc6d-4a9d-af5c-8c904ed1d504 · outbound

This paper cites Unet++: Redesigning skip connections to exploit multiscale features in image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Unet++: Redesigning skip connections to exploit multiscale features in image segmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.965253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a06937c-ea38-4884-97ae-b63398dcc3f6 · outbound

This paper cites Transfuse: Fusing transformers and cnns for medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Transfuse: Fusing transformers and cnns for medical image segmentation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.938156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9f9d59bc-961a-4b9c-8644-7d8057042f2d · outbound

This paper cites Hiformer: Hierarchical multi-scale representations using transformers for medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Hiformer: Hierarchical multi-scale representations using transformers for medical image segmentation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.912924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b5d4d9b8-52f0-4787-8ba6-65ad23db9ae2 · outbound

This paper cites Normal- ized cut loss for weakly-supervised cnn segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Normal- ized cut loss for weakly-supervised cnn segmentation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.887908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b2f82444-a42d-4eb3-8dca-8ec0101f241e · outbound

This paper cites Unsupervised Total Variation Loss for Semi-supervised Deep Learning of Semantic Segmentation.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Unsupervised Total Variation Loss for Semi-supervised Deep Learning of Semantic Segmentation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.217687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e21b86-c9a6-4243-aa50-860f6758d575 · outbound

This paper cites Gated CRF Loss for Weakly Supervised Semantic Image Segmentation.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Gated CRF Loss for Weakly Supervised Semantic Image Segmentation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.226440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1446e83-77ad-47d2-9c27-bd846159af31 · outbound

This paper cites Mumford–shah loss functional for image seg- mentation with deep learning,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Mumford–shah loss functional for image seg- mentation with deep learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.862295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ecd7b5e-1bf7-4c24-8e74-5003a16f1daa · outbound

This paper cites Weakly supervised segmentation of covid19 infection with scribble annotation on ct images,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Weakly supervised segmentation of covid19 infection with scribble annotation on ct images,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.833867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c32cf29-907d-4590-a071-44f0ca383b3a · outbound

This paper cites Trimix: A general framework for medical image segmentation from limited supervision,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Trimix: A general framework for medical image segmentation from limited supervision,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.812702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49cd8700-99cf-4fe4-bfc8-ddff9381c4b3 · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.259301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be363793-7308-4c4a-9ffa-e32c7b71aaeb · outbound

This paper cites Algorithms for the reduction of the number of points required to represent a digitized line or its caricature,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Algorithms for the reduction of the number of points required to represent a digitized line or its caricature,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.783176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a5e1c875-fb84-46c6-a69c-9d2c547ae896 · outbound

This paper cites ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.271407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f2aee68-5b67-4701-b09c-6e55c94c63ca · outbound

This paper cites Deep residual learning for image recognition,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Deep residual learning for image recognition,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.277561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0a0444d-07ea-4447-9227-4e77998a668f · outbound

This paper cites Consistency and adversarial semi-supervised learning for medical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Consistency and adversarial semi-supervised learning for medical image segmentation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.704122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ffd36197-1306-45a5-9974-22d82f22cbbe · outbound

This paper cites Cross-level contrastive learning and consistency constraint for semi-supervised med- ical image segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Cross-level contrastive learning and consistency constraint for semi-supervised med- ical image segmentation,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.678689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3e4bfb8b-8644-4e3a-a2c0-cfe1bf477f8e · outbound

This paper cites Mean teachers are better role mod- els: Weight-averaged consistency targets improve semi-supervised deep learning results,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Mean teachers are better role mod- els: Weight-averaged consistency targets improve semi-supervised deep learning results,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:09.301870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 541df896-6c9f-4127-8166-3cda6b7a2e1b · outbound

This paper cites St++: Make self- training work better for semi-supervised semantic segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation St++: Make self- training work better for semi-supervised semantic segmentation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.630892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 96cf934c-8b94-4a62-a821-4fab294dd687 · outbound

This paper cites Semi- supervised semantic segmentation with pixel-level contrastive learning from a class-wise memory bank,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Semi- supervised semantic segmentation with pixel-level contrastive learning from a class-wise memory bank,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.592444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4be61e11-65ad-49e7-8235-d776c6ee6e20 · outbound

This paper cites Multi-level attention network for retinal vessel segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Multi-level attention network for retinal vessel segmentation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.565151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a3472f2-970e-45a5-b56b-d2e753263924 · outbound

This paper cites Boxsup: Exploiting bounding boxes to super- vise convolutional networks for semantic segmentation,.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Boxsup: Exploiting bounding boxes to super- vise convolutional networks for semantic segmentation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:27:09.536274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 52a556b2-1aa6-43bd-a613-cf2cb551fe5f · outbound

This paper cites an unresolved cited work.

EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation Unresolved cited work

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T22:27:08.871384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers