Detection and recognition of rice leaf diseases using deep neural networks

Bui Hai Phong; Le Thao Nguyen Dang; Phuc Nhan Nguyen; Minh Quoc Bao Phan; Van Khuong Pham

doi:10.1117/12.3046200

19 September 2024 Detection and recognition of rice leaf diseases using deep neural networks

Bui Hai Phong, Le Thao Nguyen Dang, Phuc Nhan Nguyen, Minh Quoc Bao Phan, Van Khuong Pham

Proceedings Volume 13225, Sixth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2024); 132250D (2024) https://doi.org/10.1117/12.3046200
Event: Sixth International Conference on Image, Video Processing and Artificial Intelligence, 2024, Kuala Lumpur, Malaysia

Abstract

Rice plants have shown the crucial importance for our food supply. However, the diseases have significantly affected the rice productivity every year. The early and accurate detection of the diseases allows us to diagnose and treat the diseases efficiently. In the past few years, the advances in artificial intelligence allow us to detect and recognize the rice diseases with high performance. The paper presents a solution for the detection and recognition of rice diseases using deep neural networks. The detection module is performed using the YOLOv8 network. The recognition module is performed using the Denesenet-121 network. We have evaluated the proposed method on two datasets: the Kaggle and Vietnamese rice disease datasets. The obtained accuracy of 93% and 96% for the recognition of diseases of rice plants on Kaggle and Vietnamese datasets have shown the effectiveness of our proposed method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bui Hai Phong, Le Thao Nguyen Dang, Phuc Nhan Nguyen, Minh Quoc Bao Phan, and Van Khuong Pham "Detection and recognition of rice leaf diseases using deep neural networks", Proc. SPIE 13225, Sixth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2024), 132250D (19 September 2024); https://doi.org/10.1117/12.3046200

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KEYWORDS

Diseases and disorders

Neurological disorders

Neural networks

Education and training

Machine learning

Artificial intelligence

Diagnostics

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