IECE Transactions on Emerging Topics in Artificial Intelligence | Volume 1, Issue 1: 17-30, 2024 | DOI:10.62762/TETAI.2024.320179
Abstract
In this paper, we introduce a novel fast object detection framework, designed to meet the needs of real-time applications such as autonomous driving and robot navigation. Traditional processing methods often trade-off between accuracy and processing speed. To address this issue, we propose a hybrid data representation method that combines the computational efficiency of voxelization with the detail capture capability of direct data processing to optimize overall performance. Our detection framework comprises two main components: a Rapid Region Proposal Network (RPN) and a Refinement Detection Network (RefinerNet). The RPN is used to generate high-quality candidate regions, while the RefinerN... More >
Graphical Abstract
