Zongshuai Liu1, Xuyu Xiang1,2,*, Jiaohua Qin1, Yun Tan1, Qin Zhang1, Neal N. Xiong3
CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 457-466, 2021, DOI:10.32604/cmc.2020.012165
Abstract In recent years, with the development of machine learning and deep
learning, it is possible to identify and even control crop diseases by using electronic devices instead of manual observation. In this paper, an image recognition
method of citrus diseases based on deep learning is proposed. We built a citrus
image dataset including six common citrus diseases. The deep learning network
is used to train and learn these images, which can effectively identify and classify
crop diseases. In the experiment, we use MobileNetV2 model as the primary network and compare it with other network models in the aspect of speed,… More >
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