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InnovFaceNet: Deep Face Recognition for Industrial Environments

Author(s):Nagarjun Gururaj,Kanika Batra


In recent times the usage of intelligent systems has paved the way for many applications to be robust and self-reliant. One such popular and vastly growing technology is face recognition. Facial Recognition technology is used in security, surveillance, criminal justice systems and many other multimedia platforms. This work proposes a real-time facial recognition technology which can be used in any industrial setup eliminating manual supervision and ensuring authorized access to the personnel in the plant. Due to the recent development of the COVID-19 pandemic around the world, wearing masks has become a necessity. Our proposed facial recognition technology identifies a person wearing a mask without training or fine-tuning the original model with real-time processing of 20 FPS on a CPU and an F1 score of 95.07%. This makes our algorithm fast, secure, robust and deployable on a simple personal computer or any edge device at any industrial plant or organization.

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