Effective Skin Cancer Diagnosis Through Federated Learning and Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Effective Skin Cancer Diagnosis Through Federated Learning and Deep Convolutional Neural Networks

Published:2024-06-06 Issue:1 Volume:38 Page:
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Al-Rakhami Mabrook S.¹,AlQahtani Salman A.²,Alawwad Abdulaziz³

Affiliation:

1. Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

2. New Emerging Technologies and 5G Network and Beyond Research Chair, Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabi

3. Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2364145

Reference26 articles.

1. Malignant Nail Melanoma in a case report;Abarca J. M. H.;Journal of Pharmaceutical Negative Results,2023

2. Literature review: efficient deep neural networks techniques for medical image analysis

3. Ali R. Hardie R.C. De Silva M.S. and T.M. Kebede. 2019. Skin lesion segmentation and classification for ISIC 2018 by combining deep CNN and handcrafted features. arXiv Preprint arXiv:05730.

4. MSRNet: Multiclass Skin Lesion Recognition Using Additional Residual Block Based Fine-Tuned Deep Models Information Fusion and Best Feature Selection

5. Convolutional neural network architecture for skin cancer diagnosis;Carbonell M. C.;European Journal of Molecular Clinical Medicine,2021

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