Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

Abstract: With the emergence of various large-scale deep-learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...

Deep learning has become a transformative technology for modern weed detection, offering significant advantages over traditional machine vision in robustness, scalability, and recognition accuracy.

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 ...

Largest real-world analysis of AI-driven breast cancer screening in U.S. history 1 demonstrates increased cancer detection rate with consistent benefits across patient populations LOS ANGELES and ...

To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...

1 Ambam Computer Science and Application Laboratory & Department of Computer Engineering, Higher Institute of Transport, Logistics and Commerce, University of Ebolowa, Ebolowa, Cameroon. 2 Institut ...

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 ...

Introduction: Fish keypoint detection is a prerequisite for accurate fish behavior analysis and biomass weight estimation, and is therefore crucial for efficient and intelligent offshore aquaculture.

Abstract: Accurate and stable target detection is crucial for robotic grasping tasks under uneven lighting conditions. To address this, this paper proposes a target object detection network (YOLO-Net) ...