Paper Title

LOST PERSON IDENTIFICATION SYSTEM USING DEEP LEARNING

Article Identifiers

Registration ID: IJNRD_217880

Published ID: IJNRD2404252

DOI: Click Here to Get

Authors

N.Anithaa , P.Sainath Reddy , R.Sai Kumar , P.Kiran Kumar , P.Sairam

Keywords

Face recognition; Image processing ; Numpy; SVM ; CNN features ; Search photos ; Matplotlib Introduction Top of Form

Abstract

This paper tells a pair of novel use of deep learning methodology which is employed for identifying the reported missing children from the images of multiple youngsters available, with the assistance of face recognition. the ultimate public can upload their images of suspicious children into an everyday portal with landmarks and remarks. The photo are automatically compared with the registered photos of the missing child from the repository. Cataloging of the input child photo is performed and photo with best match are designated from the database of missing children. For this, a deep learning model is trained to properly identify the missing child from the missing child image database provided, using the facial image uploaded by the final word public. The Convolutional Neural Network (CNN), is incredibly effective deep learning technique for image based applications is adopted here for face recognition. Face descriptors are extracted from the images employing a pre-trained CNN model VGG-Face deep architecture. Compared with normal deep learning applications, our algorithm uses convolution network only as a high level feature extractor and thus the kid recognition is completed by the trained SVM classifier. Choosing the foremost effective performing CNN model for face recognition, VGG-Face and proper training of it finally ends up during a very deep learning model invariant to noise, contrast, image pose and also the age of the children and earlier methods in face recognition based missing child identification.

How To Cite (APA)

N.Anithaa, P.Sainath Reddy, R.Sai Kumar, P.Kiran Kumar, & P.Sairam (April-2024). LOST PERSON IDENTIFICATION SYSTEM USING DEEP LEARNING . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), c219-c228. https://ijnrd.org/papers/IJNRD2404252.pdf

Issue

Volume 9 Issue 4, April-2024

Pages : c219-c228

Other Publication Details

Paper Reg. ID: IJNRD_217880

Published Paper Id: IJNRD2404252

Downloads: 000121984

Research Area: Computer Science & Technology 

Country: Chennai, Tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404252.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404252

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

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