Real-Time Smart Face Security Estimation

Samyak S. Nagrare, Payal N. Kanchanwar, Prashant V. Patle, Varsha V. Ambule
International Journal of Computational and Electronic Aspects in Engineering
Volume 2: Issue 2, June 2021, pp 18-23

Author's Information
Payal N. Kanchanwar1 
Corresponding Author
1Department of Information Technology, Smt. Radhikatai Pandav College of Engineering, Nagpur, India
nnandapure@gmail.com

 Samyak S. Nagrare1, Prashant V. Patle1, Varsha V. Ambule1
1Department of Information Technology, Smt. Radhikatai Pandav College of Engineering, Nagpur, India
Research Article -- Peer Reviewed
First online on – 8 June 2021

Open Access article under Creative Commons License

Cite this article –Samyak S. Nagrare, Payal N. Kanchanwar, Prashant V. Patle, Varsha V. Ambule“Real-Time Smart Face Security Estimation”, International Journal of Computational and Electronic Aspects in Engineering, RAME Publishers, vol. 2, issue 2, pp. 18-23, 2021.
https://doi.org/10.26706/ijceae.2.2.20210408

Abstract:-
The intricacies of Sighthound's absolutely computerized age, gender, and emotion identity set of rules are defined. Our machine is constructed on numerous deep convolutional neural networks, which aren't simplest computationally green however additionally produce modern effects on quite a few aggressive benchmarks. We accumulated significant labelled datasets from all around the international to construct our progressive deep networks. We describe a methodology and an algorithm to estimate the real-time age, emotion, and gender of a human by investigating face images on a webcam. Here we discuss the CNN-based architecture to design a real-time model. Security system Emotion, age, and gender detection of facial images in webcams play an important role in many applications like security control forensics, data analysis, video observation, and human-computer interaction.
Index Terms:-
Machine Learning, Deep Learning, Convolutional Network, CNN, Gender Estimator, Age Predictor, Emotion Detector, Python
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