Object Detection based on LIDAR Temporal Pulses using Spiking Neural Networks

Understand

Neural networks has been successfully used in the processing of Lidar data, especially in the scenario of autonomous driving.

• However, existing methods heavily rely on pre-processing of the pulse signals derived from Lidar sensors and therefore result in high computational overhead and considerable latency.
• In this paper, we proposed an approach utilizing Spiking Neural Network (SNN) to address the object recognition problem directly with raw temporal pulses.
• To help with the evaluation and benchmarking, a comprehensive temporal pulses data-set was created to simulate Lidar reflection in different road scenarios.