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SOTA
Classification d'images
Image Classification On Stl 10
Image Classification On Stl 10
Métriques
Percentage correct
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
Percentage correct
Paper Title
Repository
VGG8B + LocalLearning + CO
80.75
Training Neural Networks with Local Error Signals
-
IIC
88.80
MixMatch: A Holistic Approach to Semi-Supervised Learning
-
cosine function
84.38
Image Augmentation for Object Image Classification Based On Combination of PreTrained CNN and SVM
-
NAT-M3
97.8
Neural Architecture Transfer
-
AMDIM
93.80
A Framework For Contrastive Self-Supervised Learning And Designing A New Approach
-
MP*
93.19
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring
-
ReMixMatch
94.77
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Simulated Fixations
61
A Framework For Contrastive Self-Supervised Learning And Designing A New Approach
-
An Analysis of Unsupervised Pre-training in Light of Recent Advances
70.2
An Analysis of Unsupervised Pre-training in Light of Recent Advances
-
µ2Net+ (ViT-L/16)
99.64
A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems
-
NSRL+CN(d=32)
98.34
Toward Understanding Supervised Representation Learning with RKHS and GAN
-
Exemplar CNN
75.7
Scaling the Scattering Transform: Deep Hybrid Networks
-
FixMatch (CTA)
94.83
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
FixMatch (RA)
92.02
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
NAT-M1
96.7
Neural Architecture Transfer
-
Accuracy Monitoring
68.62
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring
-
Stacked what-where AE
74.33
Scaling the Scattering Transform: Deep Hybrid Networks
-
Leapfrog
83.7
Reversible Architectures for Arbitrarily Deep Residual Neural Networks
-
wrn16/8* D1 D1 D1
88.95
General $E(2)$-Equivariant Steerable CNNs
-
ResNet18(BN, 4)
81.04
Extended Batch Normalization
-
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