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Machine learning detects weapons in real-time from surveillance footage

Researchers have developed a real-time threat detection system for surveillance cameras, utilizing machine learning to identify weapons like guns, knives, and blunt objects. The system was trained on a combined dataset of nearly 8,000 images, including a custom collection of blunt objects. A YOLOv8 model was employed for object detection, demonstrating improved accuracy and recall for blunt objects with extended training. AI

IMPACT This research could enhance public safety by enabling automated threat detection in surveillance systems.

RANK_REASON The cluster contains an academic paper detailing a new machine learning model and dataset for a specific application.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Gajendra Mandal, J. P. Patra, Priyansh Mahant ·

    Real-Time Threat Detection from Surveillance Cameras using Machine Learning

    arXiv:2606.05708v1 Announce Type: new Abstract: Ensuring public safety in densely populated urban environments remains a critical challenge, necessitating the deployment of intelligent and automated video surveillance systems. Traditional surveillance approaches rely heavily on m…

  2. arXiv cs.CV TIER_1 English(EN) · Priyansh Mahant ·

    Real-Time Threat Detection from Surveillance Cameras using Machine Learning

    Ensuring public safety in densely populated urban environments remains a critical challenge, necessitating the deployment of intelligent and automated video surveillance systems. Traditional surveillance approaches rely heavily on manual monitoring, which is inefficient and susce…