Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions-Reference-Cited by-同舟云学术

Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions

Published:2023 Issue: Volume:11 Page:140348-140381
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Noronha Stephanie S.¹^ORCID,Mehta Mayuri A.²^ORCID,Garg Dweepna³,Kotecha Ketan⁴^ORCID,Abraham Ajith⁵^ORCID

Affiliation:

1. Computer Engineering Department, Gujarat Technological University, Chandkheda, Ahmedabad, India

2. Computer Engineering Department, Sarvajanik College of Engineering and Technology, Surat, India

3. Department of Computer Engineering, Devang Patel Institute of Advance Technology and Research (DEPSTAR), Charotar University of Science and Technology (CHARUSAT), Changa, Anand, India

4. Symbiosis Centre for Applied Artificial Intelligence, Symbiosis International (Deemed University), Pune, India

5. School of Computer Science Engineering and Technology, Bennett University, Greater Noida, Uttar Pradesh, India

Funder

Analytical Center for the Government of the Russian Federation, in November 2021

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10342692.pdf?arnumber=10342692

Reference94 articles.

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5. Selective synthetic augmentation with HistoGAN for improved histopathology image classification

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