Artificial Driving based EfficientNet for Automatic Plant Leaf Disease Classification-Reference-Cited by-同舟云学术

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Artificial Driving based EfficientNet for Automatic Plant Leaf Disease Classification

Published:2023-10-04 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Kotwal Jameer Gulab,Kashyap Ramgopal,Shafi Pathan Mohd.

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-16882-w.pdf

Reference41 articles.

1. Agarwal M, Kotecha A, Deolalikar A, Kalia R, Yadav RK and Thomas A (2023) Deep learning approaches for plant disease detection: A comparative review. In 2023 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), 1–6

2. Dhaka VS, Meena SV, Rani G, Sinwar D, Ijaz MF, Woźniak M (2021) A survey of deep convolutional neural networks applied for prediction of plant leaf diseases. Sensors 21(14):4749

3. Ahmed S, Hasan MB, Ahmed T, Sony MR, Kabir MH (2022) Less is more: lighter and faster deep neural architecture for tomato leaf disease classification. IEEE Access 10:68868–68884

4. Borhani Y, Khoramdel J, Najafi E (2022) A deep learning based approach for automated plant disease classification using vision transformer. Sci Rep 12(1):11554

5. Ahmed AA, Reddy GH (2021) A mobile-based system for detecting plant leaf diseases using deep learning. AgriEngineering 3(3):478–493

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