Enhanced Missing Persons Identification System Using Ada boost K-Nearest Neighbors Algorithm

A. Alagar; U. Balaji; S.S. Barath; K. Gokul Krishnan

Research Article

Enhanced Missing Persons Identification System Using Ada boost K-Nearest Neighbors Algorithm

Paper ID 189
Volume 5, Issue 5
Pages 27-29
Published Online: September-October 2024
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Authors

A. Alagar¹
U. Balaji²
S.S. Barath³
K. Gokul Krishnan⁴

¹Assistant Professor, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India. ²³⁴ Final Year Students, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India.

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Article Information

DOI: No DOI
Published In: Volume 5, Issue 5 (2024)
Published Online: September-October 2024
Pages: 27-29
Article Type: Research Article
Check for updates: No DOI available for cross-reference

Abstract

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Abstract: Manual procedures and disjointed data frequently impede down the tracking and recovery of missing persons. By using a PyQT5-based GUI for case registration and safe data storage in a PostgreSQL database, this solution enhances identification. Through a mobile app, members of the public can anonymously share photographs. By comparing user-submitted photos with stored face encodings, the AdaBoost KNN algorithm improves matching accuracy. The process of finding missing people is greatly accelerated by automating case registration and image matching. By overcoming the shortcomings of conventional approaches in missing person investigations, this system expedites the recovery of missing persons, boosts efficiency, enhances public involvement, and protects privacy.

Enhanced Missing Persons Identification System Using Ada boost K-Nearest Neighbors Algorithm

Article Information

Abstract

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