Collaborative Identification Method for Sea Battlefield Target Based on Deep Convolutional Neural Networks

机译：基于深度卷积神经网络的海上战场目标协同识别方法

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The target identification of the sea battlefield is the prerequisite for the judgment of the enemy in the modern naval battle. In this paper, a collaborative identification method based on convolution neural network is proposed to identify the typical targets of sea battlefields. Different from the traditional single-input/single-output identification method, the proposed method constructs a multi-input/single-output co-identification architecture based on optimized convolution neural network and weighted D-S evidence theory. The simulation results show that the method has good performance and can effectively identify the target in the complex sea battlefield environment.

机译：海上战场的目标识别是现代海战中敌人判断的前提。提出了一种基于卷积神经网络的协同识别方法，以识别典型的海战场目标。与传统的单输入/单输出识别方法不同，该方法基于优化的卷积神经网络和加权D-S证据理论构造了多输入/单输出识别方法。仿真结果表明，该方法具有良好的性能，可以有效地识别复杂海上战场环境中的目标。

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《International symposium on multispectral image processing and pattern recognition》|2017年|106091A.1-106091A.8|共8页
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Guangdi Zheng; Mingbo Pan; Wei Liu; Xuetong Wu;
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Sea battlefield; Target identifiation; Collaborative identification; Convlutional neural networks;

机译：海战场;目标识别;协同识别;卷积神经网络;

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2. Research on Behaviour Recognition Method for Moving Target Based on Deep Convolutional Neural Network [J] . Jianfang Liu, Hao Zheng, Mengyi Liao 电脑和通信（英文） . 2020,第009期

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4. Collaborative Identification Method for Sea Battlefield Target Based on Deep Convolutional Neural Networks [C] . Guangdi Zheng, Mingbo Pan, Wei Liu, SPIE Conference on Multispectral Image Processing and Pattern Recognition . 2017

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Collaborative Identification Method for Sea Battlefield Target Based on Deep Convolutional Neural Networks

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