Comparative study and analysis on skin cancer detection using machine learning and deep learning algorithms

Author:

Nancy V. Auxilia Osvin,Prabhavathy P.,Arya Meenakshi S.,Ahamed B. Shamreen

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference105 articles.

1. Addi - automatic computer-based diagnosis system for dermoscopy images (n.d.) Retrieved January 7, 2023, from https://www.fc.up.pt/addi/

2. Adegun AA, Viriri S (2020) FCN-based DenseNet framework for automated detection and classification of skin lesions in dermoscopy images. IEEE Access 8:150377–150396. https://doi.org/10.1109/access.2020.3016651

3. Adjed F, Faye I, Ababsa F, Gardezi SJ, Dass SC (2016) Classification of skin cancer images using local binary pattern and SVM classifier. AIP Conf Proc 10(1063/1):4968145

4. Admisysrg, Admisysrg, 23, P. R. L. A., 30, admisysrg Author O, Author, & 30, celebrities A. (2020). Skin lesion classification based on deep ensemble Convolutional Neural Network. ISYSRG. https://isysrg.com/2020/06/17/deep-ensemble-learning-for-skin-lesions-classification-with-convolutional-neural-network/

5. Agarwal K, Singh T (2022) Classification of skin cancer images using convolutional neural networks. SSRN Electronic J. https://doi.org/10.2139/ssrn.4055037

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