基于MobileNets的果园害虫分类识别模型研究

Study on Classification and Recognition of Orchard Pests Based on MobileNets

为在小数据集上构建果园害虫分类识别模型,并在普通安卓手机运行,本研究收集了6种常见果园害虫共计3 058张图像,首先对害虫图像进行反卷积遴选,再通过Mobile Nets构建深度学习模型进行分类识别。结果表明,所构建模型在安卓手机上运行流畅,可对所采集的6种果园害虫进行识别,其准确率均在90%以上,效果良好。

In order to construct the model of orchard pest classification on the small data set and run identification of model on ordinary Android mobile phone, a total of 3 058 images of 6 common orchard pests were collected. First, the image of the pest was selected by deconvolution, and then the depth learning model was constructed by Mobile Nets. The constructed model could run well on Android mobile, and identify the selected 6 common orchard pests. The result showed that the recognition accuracy was over 90%.