Knowledge distillation plus quantization on U-Net variants, combined with custom FPGA hardware, yields 398 FPS at 204.99 Frames/J and raises mean IoU to 71.92% on CrackVision12K, an 8.82 pps gain over prior results.
Fpga implementation of 3-bit quantized cnn for semantic segmentation,
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A Case Study on Energy-Efficient Edge AI Crack Segmentation
Knowledge distillation plus quantization on U-Net variants, combined with custom FPGA hardware, yields 398 FPS at 204.99 Frames/J and raises mean IoU to 71.92% on CrackVision12K, an 8.82 pps gain over prior results.