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Stream/Area:
-
Subject:
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Paper ID:
IJSREM64271
Volume:
10 |
5 |
May 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Artificial Intelligence and Dtat Science
Suman Ramesh Tulsiani tecnical campus faculty of engineering
Artificial Intelligence and Dtat Science
Suman Ramesh Tulsiani tecnical campus faculty of engineering
Artificial Intelligence and Dtat Science
Suman Ramesh Tulsiani tecnical campus faculty of engineering
Artificial Intelligence and Dtat Science
Suman Ramesh Tulsiani tecnical campus faculty of engineering
Artificial Intelligence and Dtat Science
Suman Ramesh Tulsiani tecnical campus faculty of engineering
Artificial Intelligence and Dtat Science
Suman Ramesh Tulsiani tecnical campus faculty of engineering
The ability of machines to interpret and process visual data has greatly improved in recent years due to the quick development of deep learning and artificial intelligence (AI). The field of face recognition and detection systems is one of the most significant applications of this advancement. By accurately and efficiently analyzing facial features from photos or video streams, these systems allow machines to identify and verify people. The design and development of an AI-based face recognition and detection system that makes use of cutting-edge deep learning methods, specifically Convolutional Neural Networks (CNNs), is presented in this project. In order to identify people, the system can recognize faces in real time and compare them to a database that already exists. High performance in terms of speed, accuracy, and adaptability under various environmental conditions is the goal of the suggested solution. Security surveillance, automated attendance systems, biometric authentication, and missing person identification are just a few of the many uses for such systems. Notwithstanding its benefits, the technology also brings with it drawbacks like privacy issues, moral dilemmas, and sensitivity to lighting and occlusion. The methodology, applications, benefits, drawbacks, and potential advancements of the suggested system are all thoroughly covered in this paper.
KEYWORDS
The face recognition system that uses intelligence is a big step forward in automation. It uses learning methods to quickly and correctly identify people in real time. This system can be used in areas like security, healthcare, finance and consumer technology which shows how important it is in our daily lives. There are some problems like privacy concerns and limitations because of the environment. People are working on these issues and technology is getting better. If we use face recognition technology in a way and keep making it better it can really change the way we identify people and make our surroundings safer and more efficient. Face recognition technology has a lot of potential to make a difference, in our lives with face recognition technology.
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Publication Date
5/29/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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