LesionNet: an automated approach for skin lesion classification using SIFT features with customized convolutional neural network

LesionNet: an automated approach for skin lesion classification using SIFT features with customized convolutional neural network

Accurate detection of skin lesions through computer-aided diagnosis has emerged as a critical advancement in dermatology, addressing the inefficiencies and errors inherent in manual visual analysis. Despite the promise of automated diagnostic approaches, challenges such as image size variability, ha...

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Bibliographic Details
Main Authors: Sarah A. Alzakari, Stephen Ojo, James Wanliss, Muhammad Umer, Shtwai Alsubai, Areej Alasiry, Mehrez Marzougui, Nisreen Innab
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-10-01
Series:Frontiers in Medicine
Subjects:
skin lesion classification
computer vision
customized CNN
SIFT features
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2024.1487270/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2024.1487270/full

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