Skin Cancer Classification Utilizing a Hybrid Model of Machine Learning Models Trained on Dermoscopic Images-Reference-Cited by-同舟云学术

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Skin Cancer Classification Utilizing a Hybrid Model of Machine Learning Models Trained on Dermoscopic Images

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA)
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Author:

Ahmed Seham Gamil¹,Zeng Feng¹,Alrifaey Moath²,Ahmadipour Masoud³

Affiliation:

1. School of Computer Science and Engineering, Central South University,Changsha,China

2. Universiti Putra Malaysia,Faculty of Engineering,Department of Mechanical and Manufacturing Engineering,Serdang,Malaysia

3. School of Electrical Engineering, College of Engineering Universiti Teknologi MARA (UiTM), Shah Alam,Selangor,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10293182/10293222/10293619.pdf?arnumber=10293619

Reference21 articles.

1. Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks

2. Skin Cancer Detection Using Image Processing;ansari;International Research Journal of Engineering and Technology (IRJET),2017

3. A survey on deep learning in medical image analysis

4. Densely Connected Convolutional Networks

5. Blockchain Technology: Is It a Good Candidate for Securing IoT Sensitive Medical Data?

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Extensive Investigation into the Use of Machine Learning Tools and Deep Neural Networks for the Recognition of Skin Cancer: Challenges, Future Directions, and a Comprehensive Review;Symmetry;2024-03-18

2. Cutaneous Oncology: Strategies for Melanoma Prevention, Diagnosis, and Therapy;Cancer Control;2024-01

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