窄叶杂草 meaning in Chinese

grassy weed

The network classified over 90 % of the weed from corn seedling . and the influence of learning error and the number of hide layer nodes on network performance was also studied
试验结果表明，形状识别神经网络能正确识别玉米、阔叶杂草与窄叶杂草，识别正确率在90以上。
( 2 ) after statistical experiment on color indexes of weed images which were acquired in various illumination intensity , soil humidity and remains coverage , it pointed out that hue and relative color index are insensitive to illumination intensity , soil humidity , remains coverage and shadow , hue and excess green have a distinct contrast between plant and non - plant , but can not be used to identify corn and seed
( 2 )利用自行开发的aoi (感兴趣区域)工具，通过对不同土壤湿度、光照强度和残茬覆盖率下的杂草图像进行颜色指数测定与分析，指出色度及过绿特征对光照强度、土壤湿度、残茬覆盖率、植物阴影的影响不敏感，且在植物与非植物之间存在足够的对比度，但不能用于玉米与杂草，或阔叶杂草与窄叶杂草的识别。