Paper Title
TraceX
Article Identifiers
Authors
Seema Bhuravane , Shreya Lale , Tamanpreet Singh , Darshan Mahadik
Keywords
Facial Composite Sketch, Criminal Identification, Hand-drawn, Deep Learning, Law Enforcement.
Abstract
The paper presents a novel application aimed at enhancing the process of creating facial composite sketches for criminal identification. It addresses the inefficiencies and inaccuracies associated with existing methods such as hand-drawn sketches and limited-feature composite applications. The proposed application introduces several innovative features to overcome these limitations. Firstly, it allows users to upload hand-drawn individual facial features, which are then converted into the application's component set. Additionally, users can upload previous hand-drawn sketches for identification purposes, leveraging deep learning algorithms for improved accuracy. Furthermore, the application suggests relevant facial features based on user selections, thereby enhancing efficiency in composite creation. By offering a more realistic and user-friendly approach, this application has the potential to significantly improve law enforcement's ability to identify suspects.
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How To Cite (APA)
Seema Bhuravane, Shreya Lale, Tamanpreet Singh, & Darshan Mahadik (March-2024). TraceX. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), f748-f756. https://ijnrd.org/papers/IJNRD2403585.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : f748-f756
Other Publication Details
Paper Reg. ID: IJNRD_216724
Published Paper Id: IJNRD2403585
Downloads: 000121972
Research Area: Information TechnologyÂ
Country: Kalyan (w), Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403585.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403585
About Publisher
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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Licence
This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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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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Paper Submission Open For: September 2025
Current Issue: Volume 10 | Issue 9 | September 2025
Impact Factor: 8.76
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