关键词: 梨叶, 虫害, 识别, 卷积神经网络

Abstract:

In order to solve the problems that Yuluxiang pear has many types of leaf pests, pests spreads quickly, and it takes a long time to manually identify pear leaf pests. To realize the image automatic recognition?of the pests on the Yuluxiang pear leaves under the natural environment, TACNN Convolution?Neural?Network（TACNN） is proposed as the recognition model of pests. This article first analyzes the network structure of the Alexnet model, and uniformly process the pest image of Yuluxiang leaf collected in the field. In order to avoid the over-fitting phenomenon caused by excessively large convolution kernel parameters of the fully connected layer, by optimizing the fully connected layer and setting different neuron nodes and experimental parameters, two insect recognition models, Mid-Alexnet and TACNN, are obtained. The experimental results show that the TACNN has higher recognition accuracy compared with Alexnet and Mid-Alexnet models. The categorized average accuracy rate of TACNN is 81.18%. The TACNN can accurately distinguish three pear pests such as scarabs, psylla chinensis and pear gall midge. The model has good performance in recognition and achieves precise recognition of the pests under natural environment.

Key words: pear leaves, pests, recognition, convolutional neural network