Figure - available from: Applied Sciences
This content is subject to copyright.
Source publication
Autonomous driving technology faces significant challenges in processing complex environmental data and making real-time decisions. Traditional supervised learning approaches heavily rely on extensive data labeling, which incurs substantial costs. This study presents a complete implementation framework combining Deep Deterministic Policy Gradient (...
Similar publications
Large-scale LiDAR-based point cloud semantic segmentation is a critical challenge for autonomous driving perception. Most state-of-the-art LiDAR semantic segmentation methods rely on complex operators, such as sparse 3D convolutions or KdTree structures, which hinder their deployment on modern embedded devices. While transformer architectures have...
