基于激光荧光光谱数据的疾病模式识别

发布时间：2018-03-28 07:21

  本文选题：疾病模式识别　切入点：激光荧光　出处：《激光杂志》2017年11期

【摘要】：为了解决当前疾病模式识别过程存在的精度低,速度慢等缺陷,设计了一种基于激光荧光光谱数据的疾病模式识别方法。首先收集激光荧光光谱数据,并对其进行消噪和降维处理,然后基于处理后的激光荧光光谱数据建立疾病模式识别的分类器,最后采用疾病模式识别的实验对本文方法的有效性进行测试,其疾病模式识别的精度高达95%以上,并与其它识别方法进行对比实验,本文方法的疾病模式识别结果具有十分明显的优势,实际应用价值更高。
[Abstract]:In order to solve the problems of low precision and slow speed in the process of current disease pattern recognition, a method of disease pattern recognition based on laser fluorescence spectrum data was designed. Firstly, the laser fluorescence spectrum data were collected. Then the classification of disease pattern recognition is established based on the processed laser fluorescence spectrum data. Finally, the effectiveness of this method is tested by the experiment of disease pattern recognition. The accuracy of disease pattern recognition is up to 95%, and compared with other recognition methods, the result of disease pattern recognition in this paper has obvious advantages, and the practical application value is higher.
【作者单位】： 吉林农业大学工程技术学院;
【基金】：吉林省教育厅自然科学基金项目
【分类号】：R312;TP391.4
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本文编号：1675321