Ship Collision Avoidance Navigation Signal Recognition via Vision Sensing and Machine Forecasting

Author:

Bi Qilin1,Wang Miaohui2ORCID,Huang Yijing2,Lai Minling3,Liu Zhijun1,Bi Xiuying1

Affiliation:

1. School of Navigation, Guangzhou Maritime University, Huangpu, Guangzhou, Guangdong, China

2. State Key Laboratory of Radio Frequency Heterogeneous Integration and the Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), Shenzhen University, Shenzhen, China

3. School of Physics and Optoelectronic Engineering, Guangdong University of Technology, Guangzhou, China

Funder

Natural Science Foundation of Guangdong Province

Natural Science Foundation of Shenzhen City

Guangzhou Municipal Science and Technology Project

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Reference36 articles.

1. Passive target tracking of marine traffic ships using onboard monocular camera for unmanned surface vessel

2. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

3. Infrared moving point target detection based on spatial–temporal local contrast filter

4. Very deep convolutional networks for large-scale image recognition;simonyan;arXiv 1409 1556,2014

5. Autonomous navigation and obstacle avoidance for unmanned surface vehicles

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