An Efficient Classification of Cassava Leaf Disease using VGG 16-Reference-Cited by-同舟云学术

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An Efficient Classification of Cassava Leaf Disease using VGG 16

Published:2023-12-14 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
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Author:

Soujanya A.¹,Cherukuvada Srikanth²,Murugan V.³,Ramya Singaraju⁴,Agalya K.⁵,Gayathri S.⁶

Affiliation:

1. CVR College of Engineering,Department of Computer Science and Engineering,Ibrahimpatnam (M),Telangana

2. School of Computing, SRM Institute of Science and Technology,Department of Networking and Communications,Kattankulathur, Chennai

3. CARE College of Engineering,Department of Artificial Intelligence and Data Science,Thayanur, Trichy

4. SRM Institute of Science and Technology,School of Computing,Department of Computing Technologies,Kattankulathur, Chennai

5. Sri Eshwar College of Engineering,Department of Computer Science and Engineering,Coimbatore

6. K. Ramakrishnan College of Technology,Department of Computer Science and Engineering,Samayapuram, Trichy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10464384/10465267/10465476.pdf?arnumber=10465476

Reference10 articles.

1. Enhanced Convolutional Neural Network Model for Cassava Leaf Disease Identification and Classification

2. Evaluation of CNN Models in Identifying Plant Diseases on a Mobile Device

3. Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease Classification

4. Identification of Plant-Leaf Diseases Using CNN and Transfer-Learning Approach

5. Leaf Disease Identification using ResNet

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