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SotA/Methodology/Optical Character Recognition (OCR)/CIFAR10 (10,000)

Optical Character Recognition (OCR) on CIFAR10 (10,000)

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼AugmentationsPaperDate↕Code
1TypiClust93.2NoActive Learning on a Budget: Opposite Strategies...2022-02-06Code
2PT4AL93.1NoPT4AL: Using Self-Supervised Pretext Tasks for A...2022-01-19Code
3Learning loss91.01NoLearning Loss for Active Learning2019-05-09Code
4CoreGCN90.7NoSequential Graph Convolutional Network for Activ...2020-06-18Code
5Core-set89.92NoActive Learning for Convolutional Neural Network...2017-08-01Code
6Random Baseline (Resnet18)88.45NoTowards Robust and Reproducible Active Learning ...2020-02-21Code
7Random Baseline (VGG16)85.09NoTowards Robust and Reproducible Active Learning ...2020-02-21Code