Li-Qun Kuang

Spiking Neural Network Based on Hierarchical Residual Quantization and Temporal Error Compensation for Remote Sensing Object Detection

A spiking neural network based on hierarchical residual quantization and temporal error compensation (HRQ-TEC-SNN) and used for remote sensing object detection tasks is proposed and the model’s detection accuracy has been further improved while reducing the number of model parameters and computational costs.