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Human Pathogenic Monkeypox Disease Recognition Using Q-Learning Approach.

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第一作者： Malathi,Velu

第一单位： School of Computer Science and Engineering, Panimalar Engineering College, Poonamallee, Chennai 600123, India.

作者： Malathi,Velu ^[1] ; Rajesh Kumar,Dhanaraj ^[2] ; Balamurugan,Balusamy ^[3] ; Seifedine,Kadry ^[4] ; Yang,Yu ^[5] ; Ahmed,Nadeem ^[6] ; Hafiz Tayyab,Rauf ^[7]

作者单位： School of Computer Science and Engineering, Panimalar Engineering College, Poonamallee, Chennai 600123, India. ^[1] School of Computing Science and Engineering, Galgotias University, Greater Noida 203201, India. ^[2] Associate Dean-Student Engagement, Shiv Nadar Institution of Eminence, Delhi-National Capital Region (NCR), Gautam Buddha Nagar 201314, India. ^[3] Department of Applied Data Science, Noroff University College, 4612 Kristiansand, Norway.;Artificial Intelligence Research Center (AIRC), Ajman University, Ajman P.O. Box 346, United Arab Emirates.;Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon. ^[4] Centre for Infrastructure Engineering and Safety (CIES), The University of New South Wales, Sydney, NSW 2052, Australia. ^[5] Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia. ^[6] Centre for Smart Systems, A.I. and Cybersecurity, Staffordshire University, Stoke-on-Trent ST4 2DE, UK. ^[7]

关键词 Actor–Critic deep Q-learning network deep convolutional neural network monkeypox optimization policy gradient

DOI 10.3390/diagnostics13081491

PMID 37189591

发布时间 2023-05-19

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