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Image Classification On Tiny Imagenet 1

Metriken

Validation Acc

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Paper TitleRepository
Astroformer92.98Astroformer: More Data Might not be all you need for Classification
DeiT-B/16-D + OCD(5)92.0%OCD: Learning to Overfit with Conditional Diffusion Models
SwinV2-B + GradMatch91.90Data-Efficient Training of CNNs and Transformers with Coresets: A Stability Perspective
Swin-L91.35%Vision Transformers in 2022: An Update on Tiny ImageNet
DeiT-B/16 (PUGD)91.02%Perturbated Gradients Updating within Unit Space for Deep Learning
DeiT-B/16-D + OCD90.8%OCD: Learning to Overfit with Conditional Diffusion Models
ViT-B/16 (PUGD)90.74%Perturbated Gradients Updating within Unit Space for Deep Learning
EfficientNet-B1+DCL84.39%Direction Concentration Learning: Enhancing Congruency in Machine Learning
WaveMixLite-144/777.47%WaveMix: A Resource-efficient Neural Network for Image Analysis
Context-Aware Pipeline73.6%Context-Aware Compilation of DNN Training Pipelines across Edge and Cloud-
ResNeXt-50 (SAMix+DM)72.39--
ResNeXt-50 (SAMix)72.18%Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup
ResNeXt-50 (AutoMix+DM)71.56--
ResNeXt-50 (AutoMix)70.72%AutoMix: Unveiling the Power of Mixup for Stronger Classifiers
PreActResNet-18-370.24%MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks
ResNet18 (SAMix)68.89%Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup
ResNeXt-50 (PuzzleMix+DM)68.04--
UPANets67.67UPANets: Learning from the Universal Pixel Attention Networks
ResNet18 (AutoMix)67.33%AutoMix: Unveiling the Power of Mixup for Stronger Classifiers
DenseNet + Residual Networks60%DenseNet Models for Tiny ImageNet Classification
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