Abstract: Thermal imaging provides critical information for object detection in low-light environments. However, effectively leveraging thermal data remains challenging due to the degraded performance ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...

Abstract: The current mainstream research on color-thermal (i.e., RGB-T) object detection assumes that the RGB and thermal images are strictly aligned. However, in practical situations, due to the ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...