摘要
目标识别已经成为计算机视觉和模式识别领域的一个研究热点。但是传统的目标识别方法具有过学习和欠学习等缺点,使得目标识别无法被广泛应用。支持向量机可以有效克服这些缺点,这是因为其不仅基于统计学理论,而且可以使结构风险最小化。本文在分析舰船辐射噪声的基础上,着重研究支持向量机在目标识别中的应用。
Target recognition has become a hotspot in the field of computer vision and pattern recognition. However,the traditional target recognition method has the shortcomings of learning and omission learning, so that the target recognition can not be widely used. Support vector machines can effectively overcome these shortcomings because they are not only based on statistical theory, but also can minimize structural risk. Based on the analysis of ship radiation noise, this paper focuses on the application of support vector machine in target recognition.
出处
《舰船科学技术》
北大核心
2017年第6X期19-21,共3页
Ship Science and Technology
关键词
目标识别
舰船辐射噪声
支持向量机
不变矩
target recognition
ship radiated noise
support vector machines
invariant moments
