Design And Implementation Of An XNOR-Based Variable-Precision Object Detection Accelerator For Real-Time Edge AI Applications
A hardware-efficient object detection accelerator based on XNOR-driven variable-precision computation for real-time edge artificial intelligence that reduces arithmetic complexity, memory bandwidth, and power consumption while supporting scalable real-time object detection on FPGA-based edge platforms.