Guaishou74851/SCNet
(IJCV 2024) Self-Supervised Scalable Deep Compressed Sensing [PyTorch]
This project helps scientists, engineers, and researchers efficiently acquire and reconstruct complex signals or images with significantly less data. You input a small set of measurements from 1D, 2D, or 3D natural or scientific signals, and it outputs a high-quality reconstructed signal or image. It's designed for practitioners working with advanced imaging and sensing technologies.
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Use this if you need to reduce data acquisition time and storage costs for signals and images without sacrificing reconstruction quality, especially when ground truth data is scarce or impossible to obtain.
Not ideal if you have abundant labeled measurement-ground truth data and your primary goal is not data acquisition efficiency.
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Python
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Last pushed
Mar 09, 2025
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