Skin cancer diagnosis using convolutional neural networks for smartphone images: A comparative study

Author:

Medhat Sara,Abdel-Galil Hala,Aboutabl Amal Elsayed,Saleh Hassan

Publisher

Elsevier BV

Subject

General Medicine

Reference25 articles.

1. FCN-based DenseNet framework for automated detection and classification of skin lesions in dermoscopy images;Adegun;IEEE Access,2020

2. Deep learning from limited training data: Novel segmentation and ensemble algorithms applied to automatic melanoma diagnosis;Albert;IEEE Access,2020

3. Region-of-Interest based transfer learning assisted framework for skin cancer detection;Ashraf;IEEE Access,2020

4. Data augmentation importance for classification of skin lesions via deep learning;Ayan,2018

5. Extraction of skin lesions from non dermoscopic images using deep learning;Begum;International Journal of Research in International Journal of Research in Computer Science,2017

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2. Iterative magnitude pruning-based light-version of AlexNet for skin cancer classification;Neural Computing and Applications;2023-11-20

3. Dermatologist-Level Classification of Skin Cancer Using Cascaded Ensembling of Convolutional Neural Network;2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE);2023-11-01

4. Skin Cancer Classification with DenseNet Deep Convolutional Neural Network;2023 4th IEEE Global Conference for Advancement in Technology (GCAT);2023-10-06

5. Ensemble of Deep Convolutional Neural Networks for Multi-Class Skin Lesion Recognition Using Soft Attention;2023 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD);2023-09-21

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