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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM23540
Volume:
7 |
6 |
Jun 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Deep learning, a subset of machine learning, has shown great potential in plant disease detection in recent years, with the advantages of automatic learning and feature extraction, it has been widely concerned by academic and industrial circles. At the same time, it has also become a research hotspot in the field of agricultural plant protection, such as plant disease recognition and pest range assessment, etc. The application of deep learning in plant disease recognition can avoid the disadvantages caused by artificial selection of disease spot features, make plant disease feature extraction more objective, and improve the research efficiency and technology transformation speed. This review provides the research progress of deep learning technology in the field of crop leaf disease identification in recent years. In this paper, we will present the current trends and challenges for the detection of plant leaf disease using deep learning and advanced imaging techniques.
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Publication Date
6/15/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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