Shypd.aiThe largest open index of AI toolsUnsupervised-Classification is an Academic Research tool that provides a PyTorch implementation for learning to classify images without labels. It includes SimCLR and achieves state-of-the-art results on multiple benchmarks for unsupervised image classification.
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Unsupervised-Classification is a GitHub repository offering a PyTorch implementation of the paper "SCAN: Learning to Classify Images without Labels." This tool addresses the challenge of automatically grouping images into semantically meaningful clusters when ground-truth annotations are absent. It deviates from recent end-to-end approaches by advocating a two-step method where feature learning and clustering are decoupled. The project demonstrates significant performance improvements over state-of-the-art methods on various benchmarks, including CIFAR10, CIFAR100-20, STL10, and ImageNet. It provides code for pretext tasks (like SimCLR), clustering (SCAN), and self-labeling steps, along with pretrained models and evaluation scripts, making it a valuable resource for researchers in computer vision and unsupervised learning.
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