Research Article
Deep Learning Based Paddy Disease Classification Using Resnet-50
@INPROCEEDINGS{10.4108/eai.23-11-2023.2343203, author={Thamarai selvi S B and Thirumurugan S and Kanish P and Surya M}, title={ Deep Learning Based Paddy Disease Classification Using Resnet-50}, proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India}, publisher={EAI}, proceedings_a={IACIDS}, year={2024}, month={3}, keywords={deep learning convolutional neural network paddy disease detection agriculture}, doi={10.4108/eai.23-11-2023.2343203} }- Thamarai selvi S B
Thirumurugan S
Kanish P
Surya M
Year: 2024
Deep Learning Based Paddy Disease Classification Using Resnet-50
IACIDS
EAI
DOI: 10.4108/eai.23-11-2023.2343203
Abstract
In this research, a Convolutional Neural Network (CNN) utilizing the ResNet- 50 architecture is presented, demonstrating a noteworthy accuracy level of 97% in the classification of paddy diseases. By curating an extensive dataset of paddy disease images, employing data augmentation techniques, and tailoring the model, a practical tool for efficient disease detection and management in agriculture has been developed. The model's performance is further enhanced through a fine-tuning process that involves adjusting the learning rates of specific layers. This research not only underscores the potential of deep learning within the realm of agriculture but also contributes a valuable resource for farmers and agronomists. It provides them with a timely and precise means of paddy disease identification, ultimately leading to improved crop yields and the mitigation of losses.
