Computational Methods for Medical and Cyber Security

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Tác giả: Suhuai Luo, Kamran Shaukat

Ngôn ngữ: eng

ISBN-13: 978-3036551159

ISBN-13: 978-3036551166

ISBN: books978-3-0365-5115-9

Ký hiệu phân loại:

Thông tin xuất bản: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022

Mô tả vật lý: 1 electronic resource (228 p.)

Bộ sưu tập: Tài liệu truy cập mở

ID: 373147

Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields.
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