XNORNet and Minimum Barrier Detection for Efficient Face Recognition.

Bharadwaj, Rahul; Belavadi, Sagar V.; Sameer, G. Sai; Vinay, A.; Natarajan, S.; Murthy, K. N. Balasubramanya

doi:10.1016/j.procs.2019.05.029

Cited by 4 publications

(1 citation statement)

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“…Automatic Face Recognition as evidence and trigger for police intervention was investigated by Kotsoglou [58]. XNORNet and Minimum Barrier Detection for Efficient Face Recognition were investigated by Bharadwaj [59]. Face recognition using Radial Angle Transformation was studied by Hamdan [60].…”

Section: Face Recognitionmentioning

confidence: 99%

Vehicle Parking Security System with Face Recognition Detection Based on Eigenface Algorithm

Raharja

Fathansyah

Chamim

2021

Journal of Robotics and Control

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RFID (Radio Frequency Identification) card technology is used for intelligent parking systems. Officers no longer need to record and check manually and repeatedly every vehicle that comes in and out with this system. The system has a weakness, namely if the RFId card is dropped or lost, the person who finds it can use the card. For the purpose of increasing security for users, one of the latest technologies is the use of facial recognition methods. The eigenface algorithm system is an algorithm used for face recognition. The algorithm is used as a training process for the previously inputted employee faces. The results of the training data are stored in a database which is then used as a key to recognize the face of the owner of the motorized vehicle who took the motorcycle. In the trial results of the data application, motorized vehicle owners enter when the facial recognition level is above 70%.

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Section: Face Recognitionmentioning

confidence: 99%