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Given the extensive rice consumption across numerous nations, rice stands as one of the most cultivated crops worldwide. Understanding the stages of rice cultivation within the proposed system is essential for successful rice growth and for gaining knowledge about various diseases affecting rice. Researchers have recently devised several diagnostic techniques for identifying rice leaf diseases. A convolutional neural network (CNN) based classification approach has been formulated to categorize diseases using images of rice leaves collected from rice fields. Identifying rice leaf diseases is difficult due to their diverse nature, each exhibiting unique traits. In this paper, a system for classification of Rice Leaf Diseases is proposed. Two pre-trained models, VGG16 and MobileNet, are used as classifiers. In this system, two datasets are used for the classifier. In Datasets, rice leaf diseases are classified as Bacterial Leaf Blight, Brown Spot, Leaf Smut, Leaf Blast, Sheath Blight, and Healthy. As an evaluation, the performance of the two models is compared.

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A Technique Based on Deep Learning for Classifying Rice Leaf Disease Using Pre-trained Models

  • 会议论文

  • 发表日期：

    2025年

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  • Lai Yee Win Lwin,
  • Ah Nge Htwe

摘要

Given the extensive rice consumption across numerous nations, rice stands as one of the most cultivated crops worldwide. Understanding the stages of rice cultivation within the proposed system is essential for successful rice growth and for gaining knowledge about various diseases affecting rice. Researchers have recently devised several diagnostic techniques for identifying rice leaf diseases. A convolutional neural network (CNN) based classification approach has been formulated to categorize diseases using images of rice leaves collected from rice fields. Identifying rice leaf diseases is difficult due to their diverse nature, each exhibiting unique traits. In this paper, a system for classification of Rice Leaf Diseases is proposed. Two pre-trained models, VGG16 and MobileNet, are used as classifiers. In this system, two datasets are used for the classifier. In Datasets, rice leaf diseases are classified as Bacterial Leaf Blight, Brown Spot, Leaf Smut, Leaf Blast, Sheath Blight, and Healthy. As an evaluation, the performance of the two models is compared.