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September 10, 2025INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

Criminal Tracking Using Deep Learning for Face Recognition in Surveillance Systems

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Authors

TTT. ThiyagarajanSSSharif Dahir Siyad

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Implication

System demonstrates high accuracy in criminal identification using deep learning techniques, highlighting the role of public surveillance in enhancing security.

Key Points

  • The system automatically detects and recognizes faces in real time, improving criminal identification efforts.
  • Using CNN and other algorithms, the framework achieves robust and accurate facial recognition under various conditions.
  • Real-time analysis from CCTV footage allows timely identification of suspects, aiding law enforcement efficiency.
  • Publicly shared face detection classifiers enhance the technology's accessibility and effectiveness in surveillance applications.

Cite This Study

Thiyagarajan et al. (2025) studied this question.

synapsesocial.com/papers/68c1a40254b1d3bfb60de59ehttps://doi.org/10.55041/ijsrem51670
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Enhancing Public Safety: A Comprehensive Analysis of Crime Vision Strategies2024
  2. 2Surveillance System for Real Time High Precision Recognition of Criminal2024 · 1 citations
  3. 3Deep Learning Model Based Criminal Identifications System2024
  4. 4Criminal Recognition System2024
  5. 5FACE IDENTIFICATION SYSTEM FOR IDENTIFYING THE CRIMINALS2024