Deepmind Researchers Propose ‘ReLICv2’: Pushing The Limits of Self-Supervised ResNets

Web: https://www.reddit.com/r/computervision/comments/sal8j5/deepmind_researchers_propose_relicv2_pushing_the/

The supervised learning architectures generally require a massive amount of labeled data. Acquiring this vast amount of high-quality labeled data can turn out to be a very costly and time-consuming task. The main idea behind self-supervised methods in deep learning is to learn the patterns from a given set of unlabelled data and fine-tune the model with few labeled data. Self-supervised learning using residual networks has recently progressed, but they still underperform by a large margin corresponding to supervised residual …

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