Optimal Feature Selection and Classification Using Convolutional Neural Network-Based Plant Disease Prediction-Reference-Cited by-同舟云学术

Optimal Feature Selection and Classification Using Convolutional Neural Network-Based Plant Disease Prediction

Published:2023-02-24 Issue: Volume: Page:
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Container-title:2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS)
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Author:

Lakineni Prasanna Kumar¹,Reddy D Jayanarayana²,Chitra M.³,Umapriya R⁴,Kannan L. Vadivel⁵,Barkunan S. R.⁶

Affiliation:

1. Dadi Institute of Engineering & Technology,Department of Computer Science and Engineering,Visakhapatnam,India

2. G Pullaiah College of Engineering and Technology,Department of Computer Science and Engineering,Andhra Pradesh,India

3. Rajalakshmi Institute of Technology,Department of Electronics and Communication Engineering,Chennai,India

4. KPR Institute of Engineering and Technology,Department of Chemical Engineering,Coimbatore,India

5. PSNA College of Engineering and Technology,Department of Mechanical Engineering,Dindigul,India

6. K. Ramakrishnan College of Technology,Department of Electronics and Communication Engineering,Trichy,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099473/10099480/10099630.pdf?arnumber=10099630

Reference15 articles.

1. Plant Disease Recognition: A Large-Scale Benchmark Dataset and a Visual Region and Loss Reweighting Approach

2. A Performance-Optimized Deep Learning-Based Plant Disease Detection Approach for Horticultural Crops of New Zealand

3. LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis

4. Enhancement of power quality and energy storage using a three-terminal ultra capacitor and CCM converter for regenerative controlled electric drives;ramesh;Int J Emerg Res Manag Technol,2012

5. Bacterial Foraging Optimization Based Radial Basis Function Neural Network (BRBFNN) for Identification and Classification of Plant Leaf Diseases: An Automatic Approach Towards Plant Pathology