Non-Destructive Classification of Paddy Rice Leaf Disease Infected by Bacterial and Fungal Species Using Vision-Based Deep Learning

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-05-20 DOI:10.20965/jaciii.2023.p0333
Amir A. Bracino, D. G. Evangelista, Ronnie S. Concepcion, Elmer P. Dadios, R. R. Vicerra
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引用次数: 1

Abstract

Rice is a plant with rounded hollow articulated culms, flat, well-attached leaf blades, and terminal spikes. Its cultivation and consumption shape the culture, diet, and economy of different groups, especially in Asia. However, farmers suffer great financial losses each year due to rice disease. Therefore, the identification and classification of rice diseases are very important. Prompt, timely, and accurate disease diagnosis prevents product loss and improves crop quality. This study focuses on the classification of whether rice paddy leaf is normal or has a disease (one of the following: bacterial leaf blight (BLB), bacterial leaf streaks (BLS), bacterial panicle blight (BPB): heart, downy mildew, hispa, and rice tungro disease (RTD)) using deep learning-based algorithms such as EfficientNet-b0, MobileNet-v2, and Places365-GoogLeNet. The best model for this simulation was found to be EfficientNet-b0 with an average accuracy of 97.74%.
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基于视觉深度学习的水稻叶片细菌和真菌病害无损分类
水稻是一种具有圆形中空铰接的秆,扁平,附着良好的叶片和末端穗的植物。它的种植和消费塑造了不同群体的文化、饮食和经济,尤其是在亚洲。然而,由于水稻病害,农民每年遭受巨大的经济损失。因此,水稻病害的鉴定和分类十分重要。迅速、及时和准确的疾病诊断可防止产品损失并提高作物质量。本研究主要利用基于深度学习的算法(如EfficientNet-b0、MobileNet-v2和Places365-GoogLeNet),对水稻叶片是否正常或有疾病(以下其中一种:细菌性叶枯病(BLB)、细菌性叶条病(BLS)、细菌性穗状叶枯病(BPB):心脏病、霜霉病、hispa和水稻tungro病(RTD))进行分类。该模拟的最佳模型是EfficientNet-b0,平均准确率为97.74%。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
期刊最新文献
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