Target Fusion Detection of LiDAR and Camera Based on the Improved YOLO Algorithm
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Summary
The results show that the improved YOLO algorithm and decision level fusion have high accuracy of target detection, can meet the need of real-time, and can reduce the rate of missed detection of dim targets such as non-motor vehicles and pedestrians.
- Type
- article
- Published
- 2018-10-19
- Cited by
- 47
- References
- 31
- Access
- Open access
- OpenAlex
- https://openalex.org/W2897806143
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:69533020
Keywords
Computer science, Fuse (electrical), Artificial intelligence, Computer vision, Obstacle
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- You Only Look Once: Unified, Real-Time Object Detection
- Detection, classification and tracking of moving objects in a 3D environment
- Static Calibration and Analysis of the Velodyne HDL-64E S2 for High Accuracy Mobile Scanning
- Adaptive spatial pooling for image classification
- Voting for Voting in Online Point Cloud Object Detection
- Multi-sensor Data Fusion Based on Correlation Function and Fuzzy Clingy Degree
- 3D Lidar-based static and moving obstacle detection in driving environments: An approach based on voxels and multi-region ground planes
- 3D fully convolutional network for vehicle detection in point cloud
- ConvNets and AGMM based real-time human detection under fisheye camera for embedded surveillance
- A vision-centered multi-sensor fusing approach to self-localization and obstacle perception for robotic cars
- Multimodal vehicle detection: fusing 3D-LIDAR and color camera data
- A Real-Time Chinese Traffic Sign Detection Algorithm Based on Modified YOLOv2
- LiDAR and Camera Detection Fusion in a Real Time Industrial Multi-Sensor Collision Avoidance System
- Real-time dynamic obstacle detection and tracking using 3D Lidar
- Fast R-CNN
Cited by
- Framework comparison of neural networks for automated counting of vehicles and pedestrians
- Preceding Vehicle Detection Using Faster R-CNN Based on Speed Classification Random Anchor and Q-Square Penalty Coefficient
- An Information Entropy-Based Method of Evidential Source Separation and Refusion
- Cooperative Traffic Control Solution for Vehicle Transition from Autonomous to Manual Mode exploiting Cellular Vehicle-to-Everything (C-V2X) Technology
- Performance Study on Methanol Steam Reforming Rib Micro-Reactor with Waste Heat Recovery
- Optimized visual recognition algorithm in service robots
- Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review
- Cooperative Multi-Sensor Tracking of Vulnerable Road Users in the Presence of Missing Detections
- A Vehicle Recognition Algorithm Based on Deep Convolution Neural Network
- Vulnerable objects detection for autonomous driving: A review
- Recognizing human behaviors from surveillance videos using the SSD algorithm
- Active Exploration for Obstacle Detection on a Mobile Humanoid Robot
- FPGA Implementation of an Efficient FFT Processor for FMCW Radar Signal Processing
- Improved Shape-Based Distance Method for Correlation Analysis of Multi-Radar Data Fusion in Self-Driving Vehicle
- Pedestrian detection based on multi-layer feature fusion
- A Review of Yolo Algorithm Developments
- Evaluation of 3D Vulnerable Objects’ Detection Using a Multi-Sensors System for Autonomous Vehicles
- Distance Assessment by Object Detection—For Visually Impaired Assistive Mechatronic System
- Advanced Pedestrian State Sensing Method for Automated Patrol Vehicle Based on Multi-Sensor Fusion
- Application of Improved YOLOv5 in Aerial Photographing Infrared Vehicle Detection
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