A new multi-decision based on Bayesian decision tree algorithm for ship recognition. Issue 3 (March 2021)

• Record Type: Journal Article
• Authors: Xia, Qi; Wang, Yu; Zhou, Jian; Pei, Shengqing; Geng, Zhiqiang; Xiao, Bende; Guo, Zhihan; Shao, Aijun; Yang, Hongbo
• Is Part Of: Journal of physics. Volume 1802:Issue 3(2021)
• Publication Date: 2021-03
• Subjects: VGG -- VGG19 -- ResNet -- Bayesian decision tree -- Convolutional Neural Network(CNN); Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1802/3/032090
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Ship recognition is a key topic for intelligent shipping in canal. A new multi-decision algorithm based on Bayesian decision tree is proposed. The algorithm combine three Convolutional Neural Networks module - VGG, VGG19 and ResNet to get a better classify result. A quantization method is adopt to quantize the output of these network. A new method based on decision tree construct algorithm is proposed to improve the accurate of decision tree. In experiment, implement a various compared algorithms to prove the algorithm has better performance.