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The results show that low-bit QAT, architectural slimming, FINN folding and FIFO optimization, and moderate clock scaling can jointly provide a practical real-time detector on a small Zynq FPGA.
Achieve high-speed, low-latency object detection in autonomous systems by integrating spiking neural networks and dynamic image signal processing on an FPGA.
