HyperAI
HyperAI超神経
ホーム
ニュース
最新論文
チュートリアル
データセット
百科事典
SOTA
LLMモデル
GPU ランキング
学会
検索
サイトについて
日本語
HyperAI
HyperAI超神経
Toggle sidebar
サイトを検索…
⌘
K
ホーム
SOTA
ノイジーラベル学習
Learning With Noisy Labels On Animal
Learning With Noisy Labels On Animal
評価指標
Accuracy
ImageNet Pretrained
Network
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
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.
Previous
Next
Learning With Noisy Labels On Animal | SOTA | HyperAI超神経