An iterative pruning plus quantization co-design compresses a U-Net for hyperspectral driving-scene segmentation to 1% of its parameters, enabling a 2.86x inference speed-up on an FPGA SoC with negligible accuracy loss.
Frequency of Metamerism in Natural Scenes.Journal of the Optical Society of America A, 23(10):2359–2372, 2006
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Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach
An iterative pruning plus quantization co-design compresses a U-Net for hyperspectral driving-scene segmentation to 1% of its parameters, enabling a 2.86x inference speed-up on an FPGA SoC with negligible accuracy loss.