The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification
Open accessAbstract
Crop production can be greatly reduced due to various diseases, which seriously endangers food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional classification methods, such as naked-eye observation and laboratory tests, have many limitations, such as being time consuming and subjective. Currently, deep learning (DL) methods, especially those based on convolutional neural network (CNN), have gained widespread application in plant disease classification. They have solved or partially solved the problems of traditional classification methods and represent state-of-the-art technology in this field. In this work, we reviewed the latest CNN networks pertinent to plant leaf disease classification. We summarized DL principles involved in plant disease classification. Additionally, we summarized the main problems and corresponding solutions of CNN used for plant disease classification. Furthermore, we discussed the future development direction in plant disease classification.
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Cites
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Cited by
Alzubaidi, L., Bai, J., Al-Sabaawi, A., Santamaría, J., Albahri, A. S., Al-dabbagh, B. S. N., Fadhel, M. A., Manoufali, M., Zhang, J., Al-Timemy, A. H., et al. (2023) · Journal of Big Data · doi:10.1186/s40537-023-00727-2 · Cited by 907
Metadata
- Authors
- Lu, J., Tan, L., & Jiang, H.
- Venue
- Agriculture
- Publisher
- MDPI AG
- Published
- 2021-07-27
- Volume
- 11
- Issue
- 8
- Pages
- 707
- ISSN
- 2077-0472 (ISSN-L)
- OpenAlex
- W3185377372
- Cited by
- 529
- References
- 11
- FWCI
- 43.22
- Type
- journal article
- Language
- en
- Open access
- gold
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- Lu, J., Tan, L., & Jiang, H. (2021). Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification. Agriculture. https://doi.org/10.3390/agriculture11080707
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