Automatic detection of tomato diseases and pests based on leaf images

Abstract

There are many species of tomato diseases and pests, and the pathology of which is complex. It is difficult and error-prone to simply rely on manual identification. For the ten most common tomato diseases and pests in China, This paper explores the detection algorithms on leaf images and constructs the convolution neural network model to detect tomato pests and diseases based on VGG16[8] and transfer learning. The detection model is trained with Keras/TensorFlow deep learning framework and achieves an average classification accuracy of 89%.