Advances in Engineering Innovation

Advances in Engineering Innovation

Vol. 3, 23 October 2023


Open Access | Article

Computer vision promising innovations

Yara Maha Dolla Ali * 1
1 Capitol Technology University

* Author to whom correspondence should be addressed.

Advances in Engineering Innovation, Vol. 3, 5-8 Advances in Engineering Innovation,
Published 23 October 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yara Maha Dolla Ali. Computer vision promising innovations. AEI (2023) Vol. 3: 5-8. DOI: 10.54254/2977-3903/3/2023026.

Abstract

Computer vision, an interdisciplinary field bridging artificial intelligence and image processing, seeks to bestow machines with the capability to interpret and make decisions based on visual data. As the digital age propels forward, the ubiquity of visual content underscores the importance of efficient and effective automated interpretation. This paper delves deeply into the modern advancements and methodologies of computer vision, emphasizing its transformative role in various applications ranging from medical imaging to autonomous driving. With the increasing complexity of visual data, challenges arise pertaining to real-time processing, scalability, and the ethical implications of automated decision-making. Through an exhaustive literature review and novel experimentation, this research demystifies the multifaceted domain of computer vision, elucidating its potential and constraints. The study culminates in a visionary outlook, highlighting future avenues for research, including the fusion of augmented reality with computer vision, novel deep learning architectures, and ensuring ethical AI practices in visual interpretation.

Keywords

computer vision, artificial intelligence, real-time processing, deep learning, ethical AI

References

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Advances in Engineering Innovation (AEI)
ISBN (Print)
ISBN (Online)
Published Date
23 October 2023
Series
Advances in Engineering Innovation
ISSN (Print)
2977-3903
ISSN (Online)
2977-3911
DOI
10.54254/2977-3903/3/2023026
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated