Deep Learning-based VGG16, VGG19, and ResNet Models for Grapevine Disease Classification-Reference-Cited by-同舟云学术

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Deep Learning-based VGG16, VGG19, and ResNet Models for Grapevine Disease Classification

Published:2024-04-05 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 IEEE 9th International Conference for Convergence in Technology (I2CT)
language:
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Author:

Vats Satvik¹,Anand John²,Kukreja Vinay³,Sharma Rishabh³

Affiliation:

1. Graphic Era Hill University,Computer Science and Engineering,Dehradun,Uttarakhand,India

2. IIMT College of Engineering,Computer Science and Engineering (Artificial Intelligence),Greater Noida,Uttar Pradesh,India,201310

3. Chitkara University Institute of Engineering and Technology Chitkara University,Punjab,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10543249/10543223/10544168.pdf?arnumber=10544168

Reference21 articles.

1. A grapevine leaves dataset for early detection and classification of esca disease in vineyards through machine learning

2. VddNet: Vine Disease Detection Network Based on Multispectral Images and Depth Map

3. Early Detection of Plant Viral Disease Using Hyperspectral Imaging and Deep Learning

4. Credit Card Fraud Detection using Machine and Deep Learning Techniques

5. Comparison of Deep Neural Networks in Detecting Field Grapevine Diseases Using Transfer Learning

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