Disease detection and classification in pomegranate fruit using hybrid convolutional neural network with honey badger optimization algorithm-Reference-Cited by-同舟云学术

Disease detection and classification in pomegranate fruit using hybrid convolutional neural network with honey badger optimization algorithm

Published:2024-06-11 Issue:1 Volume:27 Page:815-837
ISSN:1094-2912
Container-title:International Journal of Food Properties
language:en
Short-container-title:International Journal of Food Properties

Author:

P Sameera¹²,A Deshpande Abhay¹

Affiliation:

1. Department of Electronics and Communication Engineering, RV College of Engineering, Bengaluru, Karnataka, India

2. Department of Electronics and Communication, BNM Institute of Technology, Bangalore, Karnataka, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10942912.2024.2365927

Reference39 articles.

1. Banana Plant Disease Classification Using Hybrid Convolutional Neural Network

2. Samajpati, B. J.; Degadwala, S. D. Hybrid Approach for Apple Fruit Diseases Detection and Classification Using Random Forest Classifier. International Conference on Communication and Signal Processing (ICCSP), IEEE: India, 2016; pp 1015–1019.

3. Fruit Disease Detection and Classification;Gaikwad S. A.;Int. Res. J. Eng. Technol.,2017

4. Global Scenario of Pomegranate (Punica Granatum L.) Culture with Special Reference to India;Chandra R.;Fruit Veg. Cereal Sci. Biotechnol.,2010

5. Dhakate, M.; Ingole, A. B. Diagnosis of Pomegranate Plant Diseases Using Neural Network. Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), IEEE: India, 2015; pp 1–4.

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