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首页> 外文会议>IFIP(International Federation for Information Processing) TC 12 International Conference on Computer and Computing Technologies in Agriculture(CCTA 2007); 20070818-20; Wuyishan(CN) >ANALYSIS AND TESTING OF WEED REAL-TIME IDENTIFICATION BASED ON NEURAL NETWORK
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ANALYSIS AND TESTING OF WEED REAL-TIME IDENTIFICATION BASED ON NEURAL NETWORK

机译：基于神经网络的杂草实时识别分析与测试

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摘要

Contrasting the two green strength genes of soil, wheat, corn, and the weed, the paper designed a system to identify the weed from the crop. It used the 2G-R-B and BP neural network, with the help of pixel-position-histogram diagram, to calculate the area and position of weeds. The result showed that it could identify the weed from the field and crop with an accuracy of 93%. The program gave the result that running time of identifying weed in wheat field was 273.31ms. As far as the corn was concerned, the time was 321.94ms, In a word, the system can satisfy the request of real-time.
机译：通过对比土壤，小麦，玉米和杂草的两个绿色强度基因，该论文设计了一种从农作物中识别杂草的系统。它使用2G-R-B和BP神经网络，借助像素位置直方图来计算杂草的面积和位置。结果表明，该方法可从田间和农作物中识别出杂草，准确度达93％。结果表明，麦田杂草鉴别运行时间为273.31ms。就玉米而言，时间为321.94ms，总而言之，系统可以满足实时性的要求。

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