A novel approach toward skin cancer classification through fused deep features and neutrosophic environment.

Abdelhafeez, Ahmed; Mohamed, Hoda K; Maher, Ali; Khalil, Nariman A

Abdelhafeez, Ahmed; Mohamed, Hoda K; Maher, Ali; Khalil, Nariman A.

Afiliación

Abdelhafeez A; Faculty of Information Systems and Computer Science, October 6th University, Cairo, Egypt.
Mohamed HK; Faculty of Engineering, Ain Shams University, Cairo, Egypt.
Maher A; Military Technical College, Cairo, Egypt.
Khalil NA; Faculty of Information Systems and Computer Science, October 6th University, Cairo, Egypt.

Front Public Health ; 11: 1123581, 2023.

Article en En | MEDLINE | ID: mdl-37139387

Asunto(s)

Melanoma; Neoplasias Cutáneas; Humanos; Neoplasias Cutáneas/diagnóstico; Melanoma/diagnóstico; Diagnóstico Diferencial; Máquina de Vectores de Soporte

Palabras clave

error-correcting output codes; fused deep features; multi-support vector machine; single-valued neutrosophic sets; skin cancer classification; transfer learning

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Melanoma Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Front Public Health Año: 2023 Tipo del documento: Article

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