Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions
Author:
Affiliation:
1. Khalifa University Center for Autonomous Robotic Systems (KU-CARS), Khalifa University,United Arab Emirates
2. Beijing Institute of Technology,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10341341/10341342/10341867.pdf?arnumber=10341867
Reference28 articles.
1. A survey of robot learning from demonstration
2. Unmanned Surface Vessel Visual Object Detection Under All-Weather Conditions with Optimized Feature Fusion Network in YOLOv4
3. A Fusion Algorithm of Object Detection and Tracking for Unmanned Surface Vehicles
4. Object Detection-Tracking Algorithm for Unmanned Surface Vehicles Based on a Radar-Photoelectric System
5. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
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