Classification of Rice Leaf Diseases Using CNN-Based Pre-Trained Models and Transfer Learning

Mavaddat, Marjan; Naderan, Marjan; Alavi, Seyyed Enayatallah

doi:10.1109/ipria59240.2023.10147178

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Cited by 3 publications

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Paddy Leaf Disease Detection Using Ensemble Stacking

Badawadagi,

Bidargaddi

et al. 2024

2024 IEEE 9th International Conference for Convergence in Technology (I2CT)

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Paddy Leaf Disease Detection Using Ensemble Stacking

Badawadagi,

Bidargaddi

et al. 2024

2024 IEEE 9th International Conference for Convergence in Technology (I2CT)

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Determination of Batch Size in Convolutional Neural Networks Applied to Philippine Rice Disease

Magboo,

Magboo

2023

2023 2nd International Conference on Ambient Intelligence in Health Care (ICAIHC)

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Enhancing Rice Leaf Disease Classification: A Customized Convolutional Neural Network Approach

Abasi,

Makhadmeh,

Alomari

et al. 2023

Sustainability

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In modern agriculture, correctly identifying rice leaf diseases is crucial for maintaining crop health and promoting sustainable food production. This study presents a detailed methodology to enhance the accuracy of rice leaf disease classification. We achieve this by employing a Convolutional Neural Network (CNN) model specifically designed for rice leaf images. The proposed method achieved an accuracy of 0.914 during the final epoch, demonstrating highly competitive performance compared to other models, with low loss and minimal overfitting. A comparison was conducted with Transfer Learning Inception-v3 and Transfer Learning EfficientNet-B2 models, and the proposed method showed superior accuracy and performance. With the increasing demand for precision agriculture, models like the proposed one show great potential in accurately detecting and managing diseases, ultimately leading to improved crop yields and ecological sustainability.

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Classification of Rice Leaf Diseases Using CNN-Based Pre-Trained Models and Transfer Learning

Cited by 3 publications

References 20 publications

Paddy Leaf Disease Detection Using Ensemble Stacking

Paddy Leaf Disease Detection Using Ensemble Stacking

Determination of Batch Size in Convolutional Neural Networks Applied to Philippine Rice Disease

Enhancing Rice Leaf Disease Classification: A Customized Convolutional Neural Network Approach

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