chengtan9907/Hyperspherical-Consistency-Regularization
The official implementation of the CVPR'2022 paper Hyperspherical Consistency Regularization.
This is a technical deep learning regularization method for researchers and practitioners working with deep learning models. It helps improve the robustness and data efficiency of deep learning models, particularly in scenarios where labeled data is scarce. By taking the outputs from a deep learning classifier and a projection head, it applies a consistency regularization to enhance model performance. This is for machine learning engineers and researchers.
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Use this if you are developing or training deep learning models and need a method to improve their robustness or performance when you have limited labeled data, or you are exploring self-supervised learning techniques.
Not ideal if you are an end-user looking for a pre-built solution for a specific task or if you do not have a strong understanding of deep learning model architectures and training processes.
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Jun 22, 2022
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