Obstacle Detection of Unmanned Surface Vessel based on Faster RCNN

Author:

Cai Jiahe1,Du Sheng1,Lu Chengda1,Xiao Bo2,Wu Min1

Affiliation:

1. School of Automation, China University of Geosciences,Wuhan,China,430074

2. Guangzhou Marine Geological Survey,Guangzhou,China,511466

Publisher

IEEE

Reference11 articles.

1. Prediction of ship collision risk based on CART;yang;IET Intelligent Transport Systems,2018

2. Feasibility study of a constrained approach for optimal path planning of the USV in a dynamic maritime environment;singh;Proceedings of the 2018 IEEE International Conference on Autonomous Robot Systems and Competitions,2018

3. Ship target detection in remote sensing images based on deep learning;zhao;Science of Surveying and Mapping,2020

4. Autonomous navigation technology of unmanned surface craft;hu;NAVIGATION AND CONTROL,2019

5. Ship detection in SAR images based on deep convolutional neural network;yang;Systems Engineering and Electronics,2019

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