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OBJECT DETECTION USING DEEP-LEARNING

  • Unique Paper ID: 165633
  • Volume: 11
  • Issue: 1
  • PageNo: 1557-1560
  • Abstract:
  • This study provides a novel method to access control systems that combines deep learning-based facial recognition technology with strong cybersecurity safeguards. The system’s goal is to improve physical security in cyber-physical environments, ensuring that only authorized persons have access to sensitive locations. The facial recognition model, which was trained on a broad dataset, uses convolutional neural networks to detect and recognize faces accurately and efficiently. To address cybersecurity issues, the project employs encryption techniques, safe data transmission, and constant threat detection. The combination of biometric authentication and cybersecurity measures provides a comprehensive solution that reduces the danger of unauthorized access while strengthening the system’s overall security posture. The project’s findings help to progress the development of advance access control solutions in modern organizational contexts, with an emphasis on both physical and digital security.
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  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 1
  • PageNo: 1557-1560

OBJECT DETECTION USING DEEP-LEARNING

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Journal no 47859

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