Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
With the increasing need for intelligent surveillance systems, our web application integrates three essential modules: motion detection, face recognition, and face mask detection. These features work together to monitor environments, identify individuals, and ensure compliance with health guidelines. The system aims to enhance security and safety across various settings by offering real-time monitoring, recognition, and alerting capabilities. This application leverages advanced algorithms such as deep learning and computer vision to improve accuracy and efficiency. It provides a scalable solution adaptable to a range of environments, from public spaces to enterprises, addressing modern challenges like identity verification and pandemic management.
Keywords: Motion Detection, Face Recognition, Face Mask Detection, Real-time Surveillance, Deep Learning, Flask Web Application, Security System, Health Compliance.
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Cite Article:
"Host-based Intrusion Detection System Specialist Using Deep Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c94-c97, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504234.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator