Innovative Applications of Machine Learning in Image Recognition

Ke Qian

doi:10.70393/6a6374616d.323533

OPEN ACCESS |Research Article ||1 January 2025

Innovative Applications of Machine Learning in Image Recognition

Ke Qian

University of Southern California

keqian@gmail.com

University of Southern California, USA.

* Corresponding Author¹: Ke Qian, E-Mail: keqian@gmail.com

Publication

Accepted Unknow ; Published 2025 January 1

Journal of Computer Technology and Applied Mathematics, 2025, 2(1), 3007-4126.

Abstract

Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation pro- gation. This paper aims to devle into the scope of applications of Machine Learning in image recgonition.

Keywords

Machine Learning , Image Recognition , Classification .

Metadata

DOI:

10.70393/6a6374616d.323533

ARK:

ark:/40704/JCTAM.v2n1a03

Pages: 15-20

References: 18

Disciplines: Artificial Intelligence and Intelligence

Subjects: Machine Learning

Cite This Article

APA Style

Qian, K. (2025). Innovative applications of machine learning in image recognition. Journal of Computer Technology and Applied Mathematics, 2(1), 15-20. https://doi.org/10.70393/6a6374616d.323533

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

FUNDING

Not applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not applicable.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

INFORMED CONSENT STATEMENT

Not applicable.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHOR CONTRIBUTIONS

Not applicable.

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Copyright © 2025 The Author(s). Published by Southern United Academy of Sciences.
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