How we built safety violations detection system
Computer vision systems allow automating a wide range of different processes related to manufacturing. We will discuss the way how we have built a real-time safety violations detection system, starting from team building and data collection to network optimization. Another crucial point of this speech will touch the difficulties encountered by our team, as well as the approaches and tools that have worked for us to address these challenges.
- Data Science Team Lead at Limpid Armor
- Master of Computer Science and Artificial Intelligence at NTUU "KPI" IASA
- Member of the AVT-290 NATO Working Group on Standardization of Augmented Reality Systems for Ground Platforms
- Main interests areas: machine learning, computer vision, management theory, neuroscience
- LinkedIn, Facebook