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vehicle detection

Papers

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Showing 126–150 of 249 papers

TitleStatusHype
PointRGCN: Graph Convolution Networks for 3D Vehicles Detection Refinement—0
POL-LWIR Vehicle Detection: Convolutional Neural Networks Meet Polarised Infrared Sensors—0
Polygon Intersection-over-Union Loss for Viewpoint-Agnostic Monocular 3D Vehicle Detection—0
Potential destination discovery for low predictability individuals based on knowledge graph—0
Probabilistic Oriented Object Detection in Automotive Radar—0
Provident Vehicle Detection at Night for Advanced Driver Assistance Systems—0
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds—0
PVSS: A Progressive Vehicle Search System for Video Surveillance Networks—0
R^3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos—0
Real-time object detection and tracking using flash LiDAR imagery—0
Real-Time Pose Estimation Piggybacked on Object Detection—0
Real-Time Vehicle Detection and Urban Traffic Behavior Analysis Based on UAV Traffic Videos on Mobile Devices—0
Reliable Traffic Monitoring Using Low-Cost Doppler Radar Units—0
Remote Detection of Idling Cars Using Infrared Imaging and Deep Networks—0
Research on vehicle detection based on improved YOLOv8 network—0
Ret3D: Rethinking Object Relations for Efficient 3D Object Detection in Driving Scenes—0
Revolutionizing Traffic Management with AI-Powered Machine Vision: A Step Toward Smart Cities—0
Robust and Fast Vehicle Detection using Augmented Confidence Map—0
Robust Detection, Association, and Localization of Vehicle Lights: A Context-Based Cascaded CNN Approach and Evaluations—0
RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection—0
SA-NET.v2: Real-time vehicle detection from oblique UAV images with use of uncertainty estimation in deep meta-learning—0
Scalable and Real-time Multi-Camera Vehicle Detection, Re-Identification, and Tracking—0
Scale Optimization for Full-Image-CNN Vehicle Detection—0
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud—0
Self-Supervised Learning for Real-World Object Detection: a Survey—0
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