Classification Of Rice Leaf Diseases Using Transfer Learning With CNN

Registration ID: IJNRD_195242

Published ID: IJNRD2305371

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M Madhav Reddy , N Sripriya , P Pavan Kalyan , Y Charan

Convolutional Neural Network, Deep Learning, Fine-Tuning, Rice Leaf Diseases, Transfer Learning

One of the most widely grown crops in India is rice, which is afflicted by a number of illnesses at different phases of its development. With their limited understanding, farmers find it extremely challenging to manually detect these diseases effectively. Recent advancements in deep learning demonstrate how Convolutional Neural Network (CN N) model-based automatic image recognition systems can be quite helpful in solving such issues. Since there aren't many image datasets available for the rice leaf disease, we developed our own, small dataset and utilised Transfer Learning to build our deep learning model. The dataset gathered from rice fields and the internet was used to train and test the suggested CNN architecture, which is based on VGG16.

Published Paper   E-Certificate

M Madhav Reddy, N Sripriya, P Pavan Kalyan, & Y Charan (May-2023). Classification Of Rice Leaf Diseases Using Transfer Learning With CNN. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), d559-d563. https://ijnrd.org/papers/IJNRD2305371.pdf

Volume 8 Issue 5, May-2023

Pages : d559-d563

Paper Reg. ID: IJNRD_195242

Published Paper Id: IJNRD2305371

Downloads: 000121976

Research Area: Computer Science & Technology 

Country: thiruvallur, tamil nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305371.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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