Accueil Actualités Articles de recherche récents Tutoriels Ensembles de données Wiki SOTA Modèles LLM Classement GPU Événements

Français

Learning With Noisy Labels On Animal

Métriques

Accuracy

ImageNet Pretrained

Network

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	ImageNet Pretrained	Network	Paper Title	Repository
Jigsaw-ViT	89.0	NO	DeiT-S	Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer	-
Cross Entropy	79.4	NO	Vgg19-BN	Learning with Feature-Dependent Label Noise: A Progressive Approach	-
Nested Dropout	81.3	NO	Vgg19-BN	Boosting Co-teaching with Compression Regularization for Label Noise	-
PLC	83.4	NO	Vgg19-BN	Learning with Feature-Dependent Label Noise: A Progressive Approach	-
C2MT	85.9	NO	Vgg-19-BN	Cross-to-merge training with class balance strategy for learning with noisy labels
CE + Dropout	81.3	NO	Vgg19-BN	Boosting Co-teaching with Compression Regularization for Label Noise	-
SURE	89.0	NO	Vgg19-BN	SURE: SUrvey REcipes for building reliable and robust deep networks	-
SELFIE	81.8	NO	Vgg19-BN	SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
PSSCL	88.74	NO	Vgg19-BN	PSSCL: A progressive sample selection framework with contrastive loss designed for noisy labels
Dynamic Loss	86.5	NO	Vgg19-BN	Dynamic Loss For Robust Learning	-
InstanceGM	84.6	NO	Vgg19-BN	Instance-Dependent Noisy Label Learning via Graphical Modelling	-
SSR	88.5	NO	Vgg19-BN	SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise	-
InstanceGM with ConvNeXt	84.7	NO	ConvNeXt	Instance-Dependent Noisy Label Learning via Graphical Modelling	-
Nested+Co-teaching (NCT)	84.1	NO	Vgg19-BN	Compressing Features for Learning with Noisy Labels	-
BtR	88.5	NO	Vgg19-BN	Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels	-
SPR	86.8	NO	VGG19-BN	Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels	-
GNL	85.9	NO	Vgg-19-BN	Partial Label Supervision for Agnostic Generative Noisy Label Learning	-
InstanceGM with ResNet	82.3	NO	ResNet	Instance-Dependent Noisy Label Learning via Graphical Modelling	-

0 of 18 row(s) selected.

Learning With Noisy Labels On Animal | SOTA | HyperAI