Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)

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Studies Advanced in Crop Disease Image Recognition

Authors
Fanyun Yang1, *
1School of Advanced Technology, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, China
*Corresponding author. Email: Fanyun.Yang20@student.xjtlu.edu.cn
Corresponding Author
Fanyun Yang
Available Online 27 November 2023.
DOI
10.2991/978-94-6463-300-9_103How to use a DOI?
Keywords
Crop disease recognition; Machine learning; Deep learning
Abstract

Crop diseases have an essential impact on food supply and agricultural productivity. Developing quick and automated technologies for crop disease diagnosis, therefore becomes crucial. Early identification of crop diseases mainly relied on field surveys by technicians, which was labor-intensive. Field agricultural disease detection has attracted a lot of scholarly interest owing to the rapid growth of technology for pattern recognition. Focusing on the above two categories of frameworks, this paper seeks to cover the most recent advances in crop disease image identification research. Specifically, representative methods are first introduced in detail, including the design ideas, key steps, advantages and disadvantages of these methods, etc. Second, the recognition accuracy of representative methods is compared to common datasets. Finally, the current hot topics in crop disease image detection are outlined, and discussion is had regarding the subject's potential future development.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)
Series
Advances in Computer Science Research
Publication Date
27 November 2023
ISBN
10.2991/978-94-6463-300-9_103
ISSN
2352-538X
DOI
10.2991/978-94-6463-300-9_103How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Fanyun Yang
PY  - 2023
DA  - 2023/11/27
TI  - Studies Advanced in Crop Disease Image Recognition
BT  - Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)
PB  - Atlantis Press
SP  - 1024
EP  - 1033
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-300-9_103
DO  - 10.2991/978-94-6463-300-9_103
ID  - Yang2023
ER  -