利用区域建议卷积神经网络中的最大锚箱定位植物叶片

debojyoti Misra, Prakash Duraisamy, Tushar Sandan
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摘要

随着地球人口的增长,对粮食的需求也成正比增长。及早、经济有效地检测植物病害可以减少全世界的粮食损失。目前基于图像的植物病害检测方法往往在田间条件下失效。我们的方法使用区域建议网络来定位病叶,以便进行检测。我们不丢弃任何先验锚框,从而提高了网络的平均召回率,使定位效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localizing plant leaves using maximum anchor boxes in region proposal convolutional neural networks
As the population of the earth grows, the demand for food grows proportionally. Early and cost-effective detection of plant diseases can result in less food loss throughout the world. The current methods for image-based plant disease detection tend to fail in field conditions. Our method uses region proposal networks to localize diseased leaves for detection. We discard no prior anchor boxes, which increases the average recall of the network, resulting in better localization.
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