Analyzing Crowds with Deep Learning: A Review of Methods and Challenges

Mohan M. Khambalkar; Pranjal Chaubey; Kalpan Shah; Rana Harshil Jayesh Kumar

International Journal of Embedded Systems and Emerging Technologies

Analyzing Crowds with Deep Learning: A Review of Methods and Challenges

Abstract

With the growing population, the need for an effective crowd management tool emerged. It is important to monitor and analyze unusual crowd movements and behavior for many applications such as peaceful events, protests, gatherings, or traffic management. Current systems, such as video surveillance, are a useful technique for crowd monitoring, but they require human visual capabilities to monitor the crowd. This work is a paper on Crowd Analysis using convolution neural networks (CNN). We present three models in this paper. First, Face Mask detection, second Object detection, and third Crowd Analysis. This work contributes towards constructing a model that works on images, video feeds, and live CCTV feeds

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How to cite

Mohan M. Khambalkar, Pranjal Chaubey, Kalpan Shah, Rana Harshil Jayesh Kumar. Analyzing Crowds with Deep Learning: A Review of Methods and Challenges. International Journal of Embedded Systems and Emerging Technologies. 2024;9(2):30–42.

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Analyzing Crowds with Deep Learning: A Review of Methods and Challenges

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