An intelligent framework for skin cancer detection and classification using fusion of Squeeze-Excitation-DenseNet with Metaheuristic-driven ensemble deep learning models

Skin cancer is the most dominant and critical method of cancer, which arises all over the world. Its damaging effects can range from disfigurement to major medical expenditures and even death if not analyzed and preserved timely. Conventional models of skin cancer recognition require a complete phys...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 7425 - 23
Hauptverfasser:	Dorathi Jayaseeli, J. D., Briskilal, J, Fancy, C., Vaitheeshwaran, V., Patibandla, R. S. M. Lakshmi, Syed, Khasim, Swain, Anil Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 03.03.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/705/117 639/705/258 Algorithms Cancer Classification Convolutional Neural Networks Deep Learning Ensemble deep learning Feature extraction Gray Wolf optimization Humanities and Social Sciences Humans Image preprocessing Image Processing, Computer-Assisted - methods Long short-term memory multidisciplinary Science Science (multidisciplinary) Skin cancer Skin Cancer detection Skin diseases Skin lesions Skin Neoplasms - classification Skin Neoplasms - diagnosis Skin Neoplasms - diagnostic imaging Ensemble deep learning Feature extraction Gray Wolf optimization Image preprocessing Skin Cancer detection
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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