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)
Real-time detection of crowds in urban and public spaces has become increasingly important for public safety, security, and traffic movement due to the large number of people congregating at transport hubs, shopping malls, stadiums, and public gatherings. This paper proposes a Crowd Detection and Density Estimation System based on state-of-the-art deep learning and computer vision techniques that can detect, analyze and quantify the density of crowds using live CCTV camera footage. The proposed approach uses a YOLO based object detection algorithm for real-time detection of persons in the scene, due to its high accuracy and low latency performance.
"Enhanced Real-Time Crowd Counting UsingYOLOv8 and DeepSORT Optimization.", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.b679-b690, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603181.pdf
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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