A Comprehensive Joint Learning System to Detect Skin Cancer-Reference-Cited by-同舟云学术

A Comprehensive Joint Learning System to Detect Skin Cancer

Published:2023 Issue: Volume:11 Page:79434-79444
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Riaz Lubna¹,Qadir Hafiz Muhammad²,Ali Ghulam¹^ORCID,Ali Mubashir³,Raza Muhammad Ahsan⁴,Jurcut Anca D.⁵^ORCID,Ali Jehad⁶^ORCID

Affiliation:

1. Department of Computer Science, University of Okara, Okara, Pakistan

2. Department of Software Engineering, Lahore Garrison University, Lahore, Pakistan

3. Center for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

4. Department of Information Sciences, University of Education, Multan Campus, Lahore, Pakistan

5. School of Computer Science, University College Dublin, Dublin 4, Ireland

6. Department of AI Convergence Network, Ajou University, Suwon, South Korea

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/ielx7/6287639/10005208/10189856.pdf?arnumber=10189856

Reference34 articles.

1. Use of Tanning Beds and Incidence of Skin Cancer

2. Deep Learning and Handcrafted Method Fusion: Higher Diagnostic Accuracy for Melanoma Dermoscopy Images

3. Gray scale and rotation invariant texture classification with local binary patterns;ojala;Proc Eur Conf Comput Vis,2000

4. AI-Skin: Skin disease recognition based on self-learning and wide data collection through a closed-loop framework

5. Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities

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