Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation | Paper Citation Record

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This paper cites In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Wein- berger, K.Q.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Wein- berger, K.Q

Reference 1

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This paper cites In: Descoteaux, M., Maier-Hein, L., Franz, A.M., Jannin, P., Collins, D.L., Duchesne, S.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Descoteaux, M., Maier-Hein, L., Franz, A.M., Jannin, P., Collins, D.L., Duchesne, S

Reference 2

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 3

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This paper cites Advances in neural information processing systems 32 (2019).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Advances in neural information processing systems 32 (2019)

Reference 4

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This paper cites In: ICASSP 2025- 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: ICASSP 2025- 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference 5

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This paper cites In: Shen, D., Liu, T., Peters, T.M., Staib, L.H., Es- sert, C., Zhou, S., Yap, P., Khan, A.R.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Shen, D., Liu, T., Peters, T.M., Staib, L.H., Es- sert, C., Zhou, S., Yap, P., Khan, A.R

Reference 6

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Observation 7bfc8786-4ae3-4ace-9a34-1dfed05a3ab7 · outbound

This paper cites In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19- 25, 2021.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19- 25, 2021

Reference 7

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This paper cites In: Proceedings of the European Conference on Computer Vision (ECCV).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Proceedings of the European Conference on Computer Vision (ECCV)

Reference 8

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This paper cites In: 31st British Machine Vision Conference 2020, BMVC 2020, Virtual Event, UK, September 7-10, 2020.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: 31st British Machine Vision Conference 2020, BMVC 2020, Virtual Event, UK, September 7-10, 2020

Reference 9

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Observation c87985bf-9378-4ce0-a263-cca63170536d · outbound

This paper cites Iranian Journal of Fuzzy Systems 19(3), 171–186 (2022).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Iranian Journal of Fuzzy Systems 19(3), 171–186 (2022)

Reference 10

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Observation 45a26429-219f-45b4-b2c9-588fea1b2d12 · outbound

This paper cites EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation

Reference 11

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This paper cites In: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Reference 12

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This paper cites Soft Computing 27(11), 6973– 6981 (2023).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Soft Computing 27(11), 6973– 6981 (2023)

Reference 13

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This paper cites Information Sciences 621, 749–765 (2023).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Information Sciences 621, 749–765 (2023)

Reference 14

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This paper cites Uncertainty-aware Evidential Fusion-based Learning for Semi-supervised Medical Image Segmentation.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Uncertainty-aware Evidential Fusion-based Learning for Semi-supervised Medical Image Segmentation

Reference 15

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This paper cites In: ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference 16

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This paper cites Pattern Recognition 166, 111639 (2025).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Pattern Recognition 166, 111639 (2025)

Reference 17

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This paper cites International Journal of Intelligent Systems 36(5), 1914–1942 (2021).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation International Journal of Intelligent Systems 36(5), 1914–1942 (2021)

Reference 18

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This paper cites Applied Intelligence 52(4), 4473–4487 (2022).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Applied Intelligence 52(4), 4473–4487 (2022)

Reference 19

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This paper cites UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration

Reference 20

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This paper cites Structured Consistency Loss for semi-supervised semantic segmentation.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Structured Consistency Loss for semi-supervised semantic segmentation

Reference 21

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This paper cites In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022

Reference 22

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This paper cites In: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Reference 23

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This paper cites In: ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2025).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2025)

Reference 24

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This paper cites In: Martel, A.L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M.A., Zhou, S.K., Racoceanu, D., Joskowicz, L.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Martel, A.L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M.A., Zhou, S.K., Racoceanu, D., Joskowicz, L

Reference 25

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

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 26

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Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Unresolved cited work

Reference 27

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This paper cites In: Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II 24.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II 24

Reference 28

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This paper cites Medical Image Analysis 80, 102517 (2022).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Medical Image Analysis 80, 102517 (2022)

Reference 29

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This paper cites In: 2016 fourth international conference on 3D vision (3DV).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: 2016 fourth international conference on 3D vision (3DV)

Reference 30

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 31

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Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Unresolved cited work

Reference 32

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This paper cites Nature Machine Intelligence 5(7), 724–738 (2023).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Nature Machine Intelligence 5(7), 724–738 (2023)

Reference 33

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This paper cites In: Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part I.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part I

Reference 34

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Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Unresolved cited work

Reference 35

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This paper cites In: Lee, D.D., Sugiyama, M., von Luxburg, U., Guyon, I., Garnett, R.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Lee, D.D., Sugiyama, M., von Luxburg, U., Guyon, I., Garnett, R

Reference 36

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This paper cites IEEE transactions on medical imaging 41(3), 608– 620 (2021).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation IEEE transactions on medical imaging 41(3), 608– 620 (2021)

Reference 37

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This paper cites Advances in neural information processing systems 30 (2017).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Advances in neural information processing systems 30 (2017)

Reference 38

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This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Proceedings of the AAAI Conference on Artificial Intelligence

Reference 39

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Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: proceedings of the IEEE/CVF international conference on computer vision

Reference 40

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This paper cites IEEE Transactions on Medical Imaging (2023).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation IEEE Transactions on Medical Imaging (2023)

Reference 41

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This paper cites In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022

Reference 42

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Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation IEEE Trans

Reference 43

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

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: International Conference on Medical Image Computing and Computer- Assisted Intervention

Reference 44

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This paper cites In: de Brui- jne, M., Cattin, P.C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y ., Essert, C.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: de Brui- jne, M., Cattin, P.C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y ., Essert, C

Reference 45

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This paper cites Medical Image Anal.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Medical Image Anal

Reference 46

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This paper cites In: International Con- ference on Medical Image Computing and Computer-Assisted Interven- tion.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: International Con- ference on Medical Image Computing and Computer-Assisted Interven- tion

Reference 47

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Observation a2334472-6131-49de-a7c6-6d37352ad544 · outbound

This paper cites Medical Image Anal.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Medical Image Anal

Reference 48

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Observation ec453902-6f53-46a0-ba8c-6f9721f6b864 · outbound

This paper cites In: Meila, M., Zhang, T.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Meila, M., Zhang, T

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:21.542373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3b386f6d-083a-459a-940f-483b2cbcfee5 · outbound

This paper cites an unresolved cited work.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Unresolved cited work

Reference 50

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b61edfc-b3a6-4b95-bfc0-86c38d5fd31d · outbound

This paper cites Frontiers in Physiology 12, 732711 (2021).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Frontiers in Physiology 12, 732711 (2021)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:21.348810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5efcaec8-bcd8-4c6b-ad23-7a16437db886 · outbound

This paper cites In: Medical Image Computing and Computer Assisted Intervention– MICCAI 2019: 22nd International Conference, Shenzhen, China, Octo- ber 13–17, 2019, Proceedings, Part II 22.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Medical Image Computing and Computer Assisted Intervention– MICCAI 2019: 22nd International Conference, Shenzhen, China, Octo- ber 13–17, 2019, Proceedings, Part II 22

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:21.150136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 66e364d3-0820-44ad-9455-9bd1e58df57c · outbound

This paper cites In: Shen, D., Liu, T., Peters, T.M., Staib, L.H., Essert, C., Zhou, S., Yap, P., Khan, A.R.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Shen, D., Liu, T., Peters, T.M., Staib, L.H., Essert, C., Zhou, S., Yap, P., Khan, A.R

Reference 53

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Source-reported events for the cited work

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Observation d1f8b35e-c645-45de-9c70-7ba801c308ed · outbound

This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:20.974078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e44c528f-d1c2-4439-b87c-fd864d48885a · outbound

This paper cites Neuroimage 31(3), 1116–1128 (2006).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation Neuroimage 31(3), 1116–1128 (2006)

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:20.775558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 90212f5c-5bda-4484-a257-cf4a8305e6f6 · outbound

This paper cites In: Ranzato, M., Beygelzimer, A., Dauphin, Y .N., Liang, P., Vaughan, J.W.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: Ranzato, M., Beygelzimer, A., Dauphin, Y .N., Liang, P., Vaughan, J.W

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:20.559300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b4c68c08-c596-488b-b84d-208855f5e397 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation mixup: Beyond Empirical Risk Minimization

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:18.946519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa3299ab-dd8c-4027-ad38-1e802c1f34c2 · outbound

This paper cites In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021.

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:20.338408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 83c2615d-287d-4d14-a669-08b9f01e0c92 · outbound

This paper cites IEEE transactions on cybernetics 50(9), 3855–3865 (2020).

Efficient Prototype Consistency Learning in Medical Image Segmentation via Joint Uncertainty and Data Augmentation IEEE transactions on cybernetics 50(9), 3855–3865 (2020)

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:20.120149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

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Outbound references

Pith citing papers