Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels | Paper Citation Record

Observation 0d91f898-3503-4f08-b006-c98181085654 · outbound

This paper cites A parametrical model for instance-dependent label noise.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(12):14055–14068, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels A parametrical model for instance-dependent label noise.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(12):14055–14068, 2023

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.328089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00ea6ba9-ee10-4bb3-a5bb-803ec9948cea · outbound

This paper cites Subclass-dominant label noise: a counterexample for the success of early stopping.Advances in Neural Information Processing Systems, 36:68343–68366, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Subclass-dominant label noise: a counterexample for the success of early stopping.Advances in Neural Information Processing Systems, 36:68343–68366, 2023

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.421671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caff4755-0dda-4857-92c7-0a99b7120aca · outbound

This paper cites Image segmentation technology based on transformer in medical decision- making system.IET Image Processing, 17(10):3040–3054, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Image segmentation technology based on transformer in medical decision- making system.IET Image Processing, 17(10):3040–3054, 2023

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.584130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f10df83-16e5-44df-82bd-10cb6d675575 · outbound

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

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels U-net: Convolutional networks for biomedical image segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.713940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cffb22f8-5aac-4076-92be-54c2d03d5fde · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Unet++: A nested u-net architecture for medical image segmentation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.845113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 329a6072-854a-4a90-be35-25b785597514 · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.Nature methods, 18(2):203–211, 2021.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.Nature methods, 18(2):203–211, 2021

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.921441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5438988-64c8-4ad5-8024-ee768807b720 · outbound

This paper cites The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific Data, 5:180161, 2018.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific Data, 5:180161, 2018

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:05.995263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aebe17ad-a54d-49ef-a897-dc382bab975f · outbound

This paper cites The multimodal brain tumor image segmentation benchmark (brats).IEEE Transactions on Medical Imaging, 34(10):1993–2024, 2015.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels The multimodal brain tumor image segmentation benchmark (brats).IEEE Transactions on Medical Imaging, 34(10):1993–2024, 2015

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.067663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf47b0ad-ae63-4444-8d8e-97b2dfdaa15a · outbound

This paper cites The liver tumor segmentation benchmark (lits).

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels The liver tumor segmentation benchmark (lits)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.131070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7d55665-9c7e-402a-89ad-78cd03c5f569 · outbound

This paper cites Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge.Medical Image Analysis, 70:101937, 2021.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge.Medical Image Analysis, 70:101937, 2021

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.176295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 781e37e4-38e3-4cee-96b6-6dddbfa29b88 · outbound

This paper cites Illumination-based transformations improve skin lesion segmentation in dermoscopic images.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Illumination-based transformations improve skin lesion segmentation in dermoscopic images

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.190386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59978337-478f-4258-9b4b-5cfe1f204429 · outbound

This paper cites Medical image segmentation: A comprehensive review of deep learning-based methods.Tomography, 11(5):52, 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Medical image segmentation: A comprehensive review of deep learning-based methods.Tomography, 11(5):52, 2025

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.267570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ad46312-daef-4452-b5c1-f13f1fdb5efd · outbound

This paper cites Augmenting Medical Imaging: A Comprehensive Catalogue of 65 Techniques for Enhanced Data Analysis.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Augmenting Medical Imaging: A Comprehensive Catalogue of 65 Techniques for Enhanced Data Analysis

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.338927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d054c599-ced0-4658-bec7-bb6b2aee5434 · outbound

This paper cites A survey on image data augmentation for deep learning.Journal of Big Data, 6(1):60, 2019.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels A survey on image data augmentation for deep learning.Journal of Big Data, 6(1):60, 2019

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.438194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 973b8c32-fadb-4205-917f-3a201321c4f5 · outbound

This paper cites Directional connectivity-based segmentation of medical images.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Directional connectivity-based segmentation of medical images

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.470653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f61b8aa6-0c15-44cc-923c-236b55a33649 · outbound

This paper cites Maxformer: Enhanced transformer for medical image segmentation with multi-attention and multi-scale features fusion.Knowledge-Based Systems, 280:110987, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Maxformer: Enhanced transformer for medical image segmentation with multi-attention and multi-scale features fusion.Knowledge-Based Systems, 280:110987, 2023

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.508404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7968c0b5-e07f-4ced-aeac-eeb302832b3a · outbound

This paper cites Translation consistent semi-supervised segmentation for 3d medical images.IEEE Transactions on Medical Imaging, 2024.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Translation consistent semi-supervised segmentation for 3d medical images.IEEE Transactions on Medical Imaging, 2024

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.561768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff6e8bde-1a18-4d1f-8574-06dacc159b96 · outbound

This paper cites Modality-agnostic domain generalizable medical image segmentation by multi-frequency in multi-scale attention.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Modality-agnostic domain generalizable medical image segmentation by multi-frequency in multi-scale attention

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.634221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5674e252-2982-4e42-81e5-7170635191df · outbound

This paper cites Condseg: A general medical image segmentation framework via contrast-driven feature enhancement.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Condseg: A general medical image segmentation framework via contrast-driven feature enhancement

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.688835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43040182-982f-4986-87ef-ccf3c61cb46a · outbound

This paper cites Eshmam Rayed, S.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Eshmam Rayed, S

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.814794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52d796d5-3ce2-4275-8cd9-8fe579313194 · outbound

This paper cites Medical image segmentation using deep learning: A survey.IET Image Processing, 16(5):1243–1267, 2022.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Medical image segmentation using deep learning: A survey.IET Image Processing, 16(5):1243–1267, 2022

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:06.938105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aceca0b6-575e-4f04-ac48-a1a2eb533ea6 · outbound

This paper cites Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends.Information Fusion, 90:316–352, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends.Information Fusion, 90:316–352, 2023

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.126259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 400afe98-4962-4910-accf-2df24ddf94f2 · outbound

This paper cites Swin SMT: Global sequential modeling for enhancing 3d medical image segmentation.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Swin SMT: Global sequential modeling for enhancing 3d medical image segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.308271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aed5de24-91a7-4f06-b8bc-d57e11ffdade · outbound

This paper cites Medical image segmentation by combining feature enhancement swin transformer and upernet.Scientific Reports, 15(14565), 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Medical image segmentation by combining feature enhancement swin transformer and upernet.Scientific Reports, 15(14565), 2025

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.524094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19eb781c-3736-470c-9fca-b0abd509d05c · outbound

This paper cites ProMISe: Prompt-driven 3d medical image segmentation using pretrained image foundation models.arXiv preprint, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels ProMISe: Prompt-driven 3d medical image segmentation using pretrained image foundation models.arXiv preprint, 2023

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.595156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffe1356c-7cd6-4fd5-85d8-e38ea02aca4e · outbound

This paper cites Medical SAM adapter: Adapting segment anything model for medical image segmentation.Medical Image Analysis, 102:103547, 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Medical SAM adapter: Adapting segment anything model for medical image segmentation.Medical Image Analysis, 102:103547, 2025

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.638764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52491179-a61f-4df7-8e95-3fa24bafd36b · outbound

This paper cites Latent diffusion for medical image segmentation: End-to-end learning for fast sampling and accuracy.arXiv preprint, 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Latent diffusion for medical image segmentation: End-to-end learning for fast sampling and accuracy.arXiv preprint, 2025

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.728349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92f879ee-128b-44db-8b79-c8b8e2950a93 · outbound

This paper cites Conditional diffusion model with spatial attention and latent embedding for medical image segmentation.arXiv preprint, 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Conditional diffusion model with spatial attention and latent embedding for medical image segmentation.arXiv preprint, 2025

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.808502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ab23c6-eaa5-4411-91eb-655a6843b7a9 · outbound

This paper cites an unresolved cited work.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.893641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d003ccc-ab8d-45ac-a4d8-91e393ee158d · outbound

This paper cites Exploring the robustness of in-context learning with noisy labels.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Exploring the robustness of in-context learning with noisy labels

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:07.936404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d019306-093a-416e-a783-ec9f26e765fa · outbound

This paper cites Estimating instance-dependent label-noise transition matrix using a deep neural network.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Estimating instance-dependent label-noise transition matrix using a deep neural network

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.005150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 980d4518-d18e-4280-8513-192daa7cf0de · outbound

This paper cites Distilling effective supervision from severe label noise.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Distilling effective supervision from severe label noise

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.083054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 357db11f-f594-431d-9e45-9486538f6f1b · outbound

This paper cites FNBench: Benchmarking Robust Federated Learning against Noisy Labels.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels FNBench: Benchmarking Robust Federated Learning against Noisy Labels

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.155262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a70adaf-0218-430c-81ee-ffdcba95f2a9 · outbound

This paper cites Dividemix: Learning with noisy labels as semi-supervised learning.ICLR, 2020.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Dividemix: Learning with noisy labels as semi-supervised learning.ICLR, 2020

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.236653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24616ce5-3889-4a51-8dad-b13ed256c8f4 · outbound

This paper cites Unicon: Combating label noise through uniform selection and contrastive learning.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Unicon: Combating label noise through uniform selection and contrastive learning

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.277725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3afa431a-c3a6-4491-b340-8f79b4f16670 · outbound

This paper cites Contrast to divide: Self-supervised pre-training for learning with noisy labels.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Contrast to divide: Self-supervised pre-training for learning with noisy labels

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.308241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e71f40ee-c07d-4e8d-874d-b2cec3b4fffe · outbound

This paper cites Adaptive integration of partial label learning and negative learning for enhanced noisy label learning.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Adaptive integration of partial label learning and negative learning for enhanced noisy label learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.350853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa59090b-82db-4fba-8a39-e97c6a743555 · outbound

This paper cites Learning to learn from noisy labeled data.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Learning to learn from noisy labeled data

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.392953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a70a795e-891e-463d-904b-810dc5023eb7 · outbound

This paper cites Advances and challenges in meta-learning: A technical review.IEEE transactions on pattern analysis and machine intelligence, 46(7):4763–4779, 2024.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Advances and challenges in meta-learning: A technical review.IEEE transactions on pattern analysis and machine intelligence, 46(7):4763–4779, 2024

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.459146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e71e3632-cf2c-4471-928a-d2c2721a66e9 · outbound

This paper cites Learning to purify noisy labels via meta soft label corrector.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Learning to purify noisy labels via meta soft label corrector

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.539022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ecff7e1-d213-4a46-8b95-7c1b3fe38499 · outbound

This paper cites an unresolved cited work.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.578072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2441ffeb-1a82-4ee3-890c-0ef01a05008d · outbound

This paper cites Learning to balance: Meta-learning for imbalanced and noisy medical image segmentation.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Learning to balance: Meta-learning for imbalanced and noisy medical image segmentation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.606515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 450e3fad-6949-4720-ba67-1f0a7a95c514 · outbound

This paper cites Joint meta-learning for robust medical image segmentation with noisy labels.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Joint meta-learning for robust medical image segmentation with noisy labels

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.649159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29761051-0c0d-4e4a-a67d-7d818c5c9d6b · outbound

This paper cites Mgl: Memory-guided learner for robust medical image segmentation with noisy labels.Medical Image Analysis, 85:102748, 2023.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Mgl: Memory-guided learner for robust medical image segmentation with noisy labels.Medical Image Analysis, 85:102748, 2023

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.695880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f327bbcd-fd63-4b48-91c7-3aaaf0081e20 · outbound

This paper cites Cmw-net: Learning a class-aware sample weighting mapping for robust deep learning.IEEE Trans.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Cmw-net: Learning a class-aware sample weighting mapping for robust deep learning.IEEE Trans

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.750708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cef172c8-82c1-4082-9353-8adb36135c38 · outbound

This paper cites Learning from noisy labels with decoupled meta label purifier.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Learning from noisy labels with decoupled meta label purifier

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.763361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa64b3e5-17f7-4208-a9e3-e226e4e581bc · outbound

This paper cites Meta label correction for noisy label learning.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Meta label correction for noisy label learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.823892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5af904c8-7619-41c2-aac7-da68514f896d · outbound

This paper cites Meta-learning collaborative optimization for lifetime prediction of lithium-ion batteries considering label noise.Journal of Energy Storage, 107:114928, 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Meta-learning collaborative optimization for lifetime prediction of lithium-ion batteries considering label noise.Journal of Energy Storage, 107:114928, 2025

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.863055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b7e18c6-f98c-4a14-bcc0-a40a25d98427 · outbound

This paper cites Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds.Reliability Engineering & System Safety, 245:110001, 2024.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds.Reliability Engineering & System Safety, 245:110001, 2024

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.920893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c80d09a7-17e8-47f0-b283-2c69cdd2498d · outbound

This paper cites Application of an electronic tongue combined with meta-learning for rice origin detection.Engineering Applications of Artificial Intelligence, 156:111174, 2025.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Application of an electronic tongue combined with meta-learning for rice origin detection.Engineering Applications of Artificial Intelligence, 156:111174, 2025

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:08.963712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 776aa3a5-c2c4-454e-89cb-a495562b8137 · outbound

This paper cites Learning to reweight examples for robust deep learning.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Learning to reweight examples for robust deep learning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:09.006894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38e60e44-fbb4-46b7-b563-55d25d459a94 · outbound

This paper cites L2b: Learning to bootstrap robust models for combating label noise.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels L2b: Learning to bootstrap robust models for combating label noise

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:09.056319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae3a41ef-bfa8-48b6-ad6a-b7934a72a5e6 · outbound

This paper cites Pixel difference networks for efficient edge detection.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Pixel difference networks for efficient edge detection

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:09.091772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f88716b4-537f-4a56-b8be-a9486b215d76 · outbound

This paper cites A large annotated medical image dataset for the development and evaluation of segmentation algorithms.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:09.163067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfd74ac9-30b1-43dc-9408-e3bb45900b24 · outbound

This paper cites Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge.Medical Image Analysis, 18(2):359–373, 2014.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge.Medical Image Analysis, 18(2):359–373, 2014

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:09.190540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdb7d87f-3511-4eae-a211-b71ef2bf032b · outbound

This paper cites Smedsrud, Michael A.

Not All Pixels Are Equal: Pixel-wise Meta-Learning for Medical Segmentation with Noisy Labels Smedsrud, Michael A

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T20:42:09.255265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers