HECNNet: Hybrid Ensemble Convolutional Neural Network Model with Multi-Backbone Feature Extractors for Soybean Disease Classification-Reference-Cited by-同舟云学术

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HECNNet: Hybrid Ensemble Convolutional Neural Network Model with Multi-Backbone Feature Extractors for Soybean Disease Classification

Published:2024-01-04 Issue: Volume:10 Page:813-818
ISSN:
Container-title:2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)
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Author:

Tiwari Raj Gaurang¹,Maheshwari Himani²,Agarwal Ambuj Kumar³,Jain Vishal³

Affiliation:

1. Chitkara University institute of Engineering and Technology, Chitkara University,Punjab,India

2. School of Computing, Graphic Era Hill University,Dehradun,Uttrakhand,India

3. School of Engineering and Technology, Sharda University,Department of Computer Science and Engineering,Greater Noida,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10467178/10467214/10467804.pdf?arnumber=10467804

Reference22 articles.

1. Rice Leaf Disease Detection: A Review

2. Identify and Classify CORN Leaf Diseases Using a Deep Neural Network Architecture

3. Optimized Transfer Learning for Dog Breed Classification;Agarwal;International Journal of Intelligent Systems and Applications in Engineering,2022

4. Image Embedding and Classification using Pre-Trained Deep Learning Architectures

5. Performance Evaluation of Optimizers in the Classification of Marble Surface Quality Using CNN

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