A Regularized CNN-SVM Framework for Improved Diagnosis of Citrus Fruit Diseases, both Common and Exotic-Reference-Cited by-同舟云学术

A Regularized CNN-SVM Framework for Improved Diagnosis of Citrus Fruit Diseases, both Common and Exotic

Published:2023-06-14 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS)
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Author:

Banerjee Deepak¹,Kukreja Vinay¹,Jain Nitin²,Vats Satvik³,Tanwar Sarvesh⁴

Affiliation:

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

2. Career Development Centre, Manav Rachna International Institute of Research and Studies,Faridabad, Haryana, India

3. Computer Science and Engineering, Graphic Era Hill University, Dehradun

4. Amity Institute of Information Technology, Amity University, Noida

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10169129/10169119/10169629.pdf?arnumber=10169629

Reference17 articles.

1. Automated Systems Based on Machine Vision for Inspecting Citrus Fruits from the Field to Postharvest—a Review

2. Citrus disease detection and classification using end-to-end anchor-based deep learning model

3. Deep Metric Learning Based Citrus Disease Classification With Sparse Data

4. Disease detection and physical disorders classification for citrus fruit images using convolutional neural network;u?uz;Journal of Food Measurement & Characterization,2022

5. An automated detection and classification of citrus plant diseases using image processing techniques: A review

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