Text

Computational Methods for Medical and Cyber Security

---

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.

---

Availability

No copy data

Detail Information

Series Title

-

Call Number

-

Publisher

: ., 2022

Collation

-

Language

ISBN/ISSN

9783036551159

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

-

Subject(s)

-

Specific Detail Info

-

Statement of Responsibility

Luo, Suhua

Other Information

Cataloger

Heri

Source

-

Validator

-

Digital Object Identifier (DOI)

10.3390/books978-3-0365-5115-9

Journal Volume

-

Journal Issue

-

Subtitle

-

Parallel Title

-

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment