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Weapon Detection Solution via Deep Learning Containerized Applications

A case study of Quality Engineering

The client is US based leading semiconductor and software company having expertise into CPUs, GPUs, SoCs, NIC, Embedded processors, Cloud and Edge Computing Platforms. With their technological advancement and product innovation they cater services across domains like smart electronics, data centers, gaming and more. The client approached Softnautics to help them build quickly deployable deep learning based weapon detection application which is compatible with their GPU platform. The solution is targeted to Security & Surveillance, Video Forensic and Home Automation industry to identify potential threats and ensure safety and security in premises. Weapon detection is of vital importance from security aspects today and early detection can avoid major crisis in sensitive establishments and neighborhoods. Along with real time surveillance to video forensics of shooting incidences and cctv footages, weapon detection is critical to success of security solutions.
  • Achieved the deep learning model accuracy as high as 96.5%
    Semiconductor
  • Faster deployment and scalability of containerized application
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