Research on the Classification of Rice Leaf Disease Images Based on Deep Learning

DOI

10.2991/978-94-6463-823-3_58How to use a DOI?

Keywords

Deep learning; Ensemble learning; Image classification; Rice leaf disease recognition

Abstract

With the advancement of artificial intelligence, computer vision technologies have been widely adopted. Particularly in plant pathology, rapid and accurate disease identification has become crucial for improving crop yields. The purpose of this paper is to explore the application of deep learning in the field of rice leaf disease recognition. Firstly, this paper presents the existing challenges for rice leaf disease identification and suggests computer vision-based image classification methods as a solution. Subsequently, it details ensemble learning’s principles and benefits, employing dataset optimization and generalization to prevent model overfitting. Then, multiple neural network models are trained, and the three models with excellent performance are integrated. This integration process ultimately validates the ensemble model’s superior performance in this task. Finally, the results show that the proposed ensemble neural network model achieves a high accuracy of 99.3% in the rice leaf disease classification task. This study not only provides technical support for rice leaf disease diagnosis but also offers valuable references for the intelligent identification of other crop diseases. In the future, the model is expected to be further optimized and extended to enable the detection of additional rice leaf diseases and adaptation to broader application scenarios.

Copyright

© 2025 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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TY  - CONF
AU  - Lejun He
PY  - 2025
DA  - 2025/08/31
TI  - Research on the Classification of Rice Leaf Disease Images Based on Deep Learning
BT  - Proceedings of the 2025 3rd International Conference on Image, Algorithms, and Artificial Intelligence (ICIAAI 2025)
PB  - Atlantis Press
SP  - 580
EP  - 586
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-823-3_58
DO  - 10.2991/978-94-6463-823-3_58
ID  - He2025
ER  -