Abstract

Plant diseases and insect pests are common factors affecting plant growth, which is directly harmful to the quality of agricultural production. In order to identify and classify plant diseases and insect pests, in this paper, a detection method based on convolutional neural network (CNN) is proposed. Specifically, this paper first introduces the processes of plant diseases and insect pests data collection, and then the methodology for training detection model based on CNN is described. Finally, a series of comparative experiments are conducted to demonstrate the effectiveness of our model, and experimental results show our model achieves competitive performance on plant diseases and insect pests dataset.

Details

Title
Research on plant diseases and insect pests identification based on CNN
Author
Tian, L G 1 ; Liu, C 1 ; Liu, Y 2 ; M Li 1 ; Zhang, J Y 1 ; Duan, H L 1 

 Tianjin Key Laboratory of Information Sensing & Intelligent Control, Tianjin University of Technology and Education, Tianjin, 300222, China 
 Tianjin Modern Vocational Technology College, Tianjin 300350 China 
Publication year
2020
Publication date
Dec 2020
Publisher
IOP Publishing
ISSN
17551307
e-ISSN
17551315
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2556417475
Copyright
© 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.