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Noise2Sim – Similarity-based Self-Learning for Image Denoising
RPI ID: 2021-034-401 Innovation Summary: Noise2Sim is a self-supervised image denoising method that leverages similarity-based learning without requiring clean reference images. The algorithm identifies consistent patterns across noisy inputs and uses them to reconstruct cleaner outputs. It is particularly effective in medical and scientific imaging...
Published: 3/10/2026   |   Inventor(s): Chuang Niu, Ge Wang
Keywords(s): deep learning, Image Denoising, self-learning, self-similarity
Category(s): Computational Science and Engineering