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SotA/Computer Vision/Image Classification/Caltech-101

Image Classification on Caltech-101

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼Extra DataPaperDate↕Code
1Pre trained wide-resnet-10197.76NoProgressiveSpinalNet architecture for FC layers2021-03-21Code
2Wide-ResNet-101 (Spinal FC)97.32YesSpinalNet: Deep Neural Network with Gradual Input2020-07-07Code
3ResNeXt-101-32x8d95.58NoDead Pixel Test Using Effective Receptive Field2021-08-31Code
4Bamboo (ViT-B/16)94.8YesBamboo: Building Mega-Scale Vision Dataset Conti...2022-03-15Code
5SEER (RegNet10B - linear eval)91YesVision Models Are More Robust And Fair When Pret...2022-02-16Code
6UL-Hopfield (ULH)91NoUnsupervised Learning using Pretrained CNN and A...2018-05-02-