Entropy‐controlled deep features selection framework for grape leaf diseases recognition-Reference-Cited by-同舟云学术

Entropy‐controlled deep features selection framework for grape leaf diseases recognition

Published:2020-05-13 Issue: Volume: Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Adeel Alishba¹,Khan Muhammad Attique²,Akram Tallha³,Sharif Abida⁴,Yasmin Mussarat¹^ORCID,Saba Tanzila⁵,Javed Kashif⁶

Affiliation:

1. Department of Computer Science COMSATS University Islamabad, Wah Campus Islamabad Pakistan

2. Department of Computer Science HITEC University Taxila Rawalpindi Pakistan

3. Department of Electrical and Computer Engineering COMSATS University Islamabad, Wah Campus Islamabad Pakistan

4. Department of Computer Science COMSATS University Islamabad, Vehari Campus Vehari Pakistan

5. Department of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia

6. Department of Robotics SMME NUST Islamabad Pakistan

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12569

Reference66 articles.

1. Automated Detection of Alzheimer’s Disease Using Brain MRI Images– A Study with Various Feature Extraction Techniques

2. Diagnosis and recognition of grape leaf diseases: An automated system based on a novel saliency approach and canonical correlation analysis based multiple features fusion

3. Agrawal N. Singhai J. &Agarwal D. K.(2017).Grape leaf disease detection and classification using multi‐class support vector machine. Paper presented at the Recent Innovations in Signal processing and Embedded Systems (RISE) 2017 International Conference on.

4. Amara J. Bouaziz B. &Algergawy A.(2017).A Deep Learning‐based Approach for Banana Leaf Diseases Classification. Paper presented at the BTW (Workshops).

5. Big data analysis for brain tumor detection: Deep convolutional neural networks

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