Open AccessReview of Crop Disease and Pest Image Recognition Technology
Author(s) -
Shaopeng Jia,
Hewei Gao
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/799/1/012045
Subject(s) - agriculture , identification (biology) , crop , image processing , agricultural engineering , agricultural pest , digital image , digital image processing , computer science , artificial intelligence , business , data science , image (mathematics) , geography , engineering , biology , ecology , forestry , archaeology
Throughout the history of agricultural development, crop diseases and pests have been one of the main obstacles hindering the development of agricultural economy, which not only caused irreversible economic losses to farmers, but also hindered the development of economic and social. The crop pets and diseases identification system based on digital image processing technology has the characteristics of fast, accurate and real-time, which can assist farmers to take effective control measures in time. In this paper, we have done some review on different digital image processing techniques to detect the plant diseases. We compared traditional machine learning and deep learning and discussed the future research trends and directions .