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Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

https://doi.org/10.5555/3327757.3327944
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CASSOR: Class-Aware Sample Selection for Ordinal Regression with Noisy Labels
inferred← citeshttps://doi.org/10.1007/978-981-99-8132-8_35openalex-snapshot
Mutually Guided Dendritic Neural Models
inferred← citeshttps://doi.org/10.1007/978-981-99-8138-0_6openalex-snapshot
Sample Selection Based on Uncertainty for Combating Label Noise
inferred← citeshttps://doi.org/10.1007/978-981-99-8148-9_14openalex-snapshot
Joint Regularization Knowledge Distillation
inferred← citeshttps://doi.org/10.1007/978-981-99-8181-6_19openalex-snapshot
All You See Is the Tip of the Iceberg: Distilling Latent Interactions Can Help You Find Treasures
inferred← citeshttps://doi.org/10.1007/978-981-99-8388-9_27openalex-snapshot
Gemini: A Dual-Task Co-training Model for Partial Label Learning
inferred← citeshttps://doi.org/10.1007/978-981-99-8435-0_1openalex-snapshot
Loss Filtering Factor for Crowd Counting
inferred← citeshttps://doi.org/10.1007/978-981-99-8435-0_2openalex-snapshot
Classifier Decoupled Training for Black-Box Unsupervised Domain Adaptation
inferred← citeshttps://doi.org/10.1007/978-981-99-8469-5_23openalex-snapshot
ASM: Adaptive Sample Mining for In-The-Wild Facial Expression Recognition
inferred← citeshttps://doi.org/10.1007/978-981-99-8543-2_2openalex-snapshot
NCMatch: Semi-supervised Learning with Noisy Labels via Noisy Sample Filter and Contrastive Learning
inferred← citeshttps://doi.org/10.1007/978-981-99-8552-4_23openalex-snapshot
Generalized Zero-Shot Learning with Noisy Labeled Data
inferred← citeshttps://doi.org/10.1007/s00357-024-09489-9openalex-snapshot
Combining Semi-supervised Clustering and Classification Under a Generalized Framework
inferred← citeshttps://doi.org/10.1007/s00371-026-04637-1openalex-snapshot
Easr: expression aware supervision and refinement for in-the-wild facial expression recognition
inferred← citeshttps://doi.org/10.1007/s00521-019-04332-4openalex-snapshot
Deep Bayesian Self-Training
inferred← citeshttps://doi.org/10.1007/s00778-022-00775-9openalex-snapshot
Data collection and quality challenges in deep learning: a data-centric AI perspective
inferred← citeshttps://doi.org/10.1007/s10009-023-00701-6openalex-snapshot
The power of typed affine decision structures: a case study
inferred← citeshttps://doi.org/10.1007/s10489-025-06690-0openalex-snapshot
A new class correlation-based dynamic sample weighting method for medical image classification
inferred← citeshttps://doi.org/10.1007/s10515-024-00453-wopenalex-snapshot
Data cleaning and machine learning: a systematic literature review
inferred← citeshttps://doi.org/10.1007/s10686-021-09757-1openalex-snapshot
MeerCRAB: MeerLICHT classification of real and bogus transients using deep learning
inferred← citeshttps://doi.org/10.1007/s10844-025-00930-yopenalex-snapshot
Self-training dual-network for denoising federated recommendation
inferred← citeshttps://doi.org/10.1007/s10994-021-06081-9openalex-snapshot
Improving deep label noise learning with dual active label correction
inferred← citeshttps://doi.org/10.1007/s10994-022-06184-xopenalex-snapshot
Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification
inferred← citeshttps://doi.org/10.1007/s10994-022-06197-6openalex-snapshot
Towards harnessing feature embedding for robust learning with noisy labels
inferred← citeshttps://doi.org/10.1007/s10994-022-06207-7openalex-snapshot
An instance-dependent simulation framework for learning with label noise
inferred← citeshttps://doi.org/10.1007/s10994-022-06211-xopenalex-snapshot
Beyond confusion matrix: learning from multiple annotators with awareness of instance features
inferred← citeshttps://doi.org/10.1007/s10994-023-06313-0openalex-snapshot
ProtoSimi: label correction for fine-grained visual categorization
inferred← citeshttps://doi.org/10.1007/s10994-023-06437-3openalex-snapshot
Nrat: towards adversarial training with inherent label noise
inferred← citeshttps://doi.org/10.1007/s10994-024-06598-9openalex-snapshot
A class sensitivity feature guided T-type generative model for noisy label classification
inferred← citeshttps://doi.org/10.1007/s10994-024-06668-yopenalex-snapshot
Probabilistic instance dependent label refinement for noisy label learning
inferred← citeshttps://doi.org/10.1007/s10994-024-06678-wopenalex-snapshot
Sandbox: safeguarded multi-label learning through safe optimal transport
inferred← citeshttps://doi.org/10.1007/s10994-024-06695-9openalex-snapshot
Let the noise flow away: combating noisy labels using normalizing flows
inferred← citeshttps://doi.org/10.1007/s11042-021-10760-zopenalex-snapshot
Ensemble diversified learning for image classification with noisy labels
inferred← citeshttps://doi.org/10.1007/s11042-024-20142-wopenalex-snapshot
A cross-domain person re-identification algorithm based on distribution-consistency and multi-label collaborative learning
inferred← citeshttps://doi.org/10.1007/s11063-021-10455-4openalex-snapshot
Multitask Classification Method Based on Label Correction for Breast Tumor Ultrasound Images
inferred← citeshttps://doi.org/10.1007/s11263-022-01575-yopenalex-snapshot
GhostNets on Heterogeneous Devices via Cheap Operations
inferred← citeshttps://doi.org/10.1007/s11263-022-01591-yopenalex-snapshot
Visual Attention Consistency for Human Attribute Recognition
inferred← citeshttps://doi.org/10.1007/s11263-022-01726-1openalex-snapshot
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data
inferred← citeshttps://doi.org/10.1007/s11263-022-01738-xopenalex-snapshot
Semi-Supervised and Long-Tailed Object Detection with CascadeMatch
inferred← citeshttps://doi.org/10.1007/s11263-023-01969-6openalex-snapshot
Delving into Identify-Emphasize Paradigm for Combating Unknown Bias
inferred← citeshttps://doi.org/10.1007/s11263-024-01997-wopenalex-snapshot
Robust Object Re-identification with Coupled Noisy Labels
inferred← citeshttps://doi.org/10.1007/s11263-024-02012-yopenalex-snapshot
Does Confusion Really Hurt Novel Class Discovery?
inferred← citeshttps://doi.org/10.1007/s11263-024-02117-4openalex-snapshot
Generalized Out-of-Distribution Detection: A Survey
inferred← citeshttps://doi.org/10.1007/s11263-024-02139-yopenalex-snapshot
Visual Out-of-Distribution Detection in Open-Set Noisy Environments
inferred← citeshttps://doi.org/10.1007/s11263-024-02187-4openalex-snapshot
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels
inferred← citeshttps://doi.org/10.1007/s11263-024-02299-xopenalex-snapshot
Instance-dependent Label Distribution Estimation for Learning with Label Noise
inferred← citeshttps://doi.org/10.1007/s11263-024-02324-zopenalex-snapshot
Combating Label Noise with a General Surrogate Model for Sample Selection
inferred← citeshttps://doi.org/10.1007/s11263-025-02494-4openalex-snapshot
RML++: Regroup Median Loss for Combating Label Noise
inferred← citeshttps://doi.org/10.1007/s11276-025-03903-9openalex-snapshot
Co-active: an efficient selective relabeling model for resource constrained edge AI
inferred← citeshttps://doi.org/10.1007/s11431-021-2139-0openalex-snapshot
Label-noise robust classification with multi-view learning
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