Journal of Hospitality Application and Research

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Biometric Face Recognition: Application of Neural Networks and Fuzzy Control in Hospitality Industry


Affiliations
1 B.Tech, Vellore Institute of Technology, Vellore, Tamil Nadu, India
2 Associate Professor, School of Business Management, NMIMS University, Mumbai, Maharashtra, India
3 B Tech, Vellore Institute of Technology, Vellore, Tamil Nadu, India
     

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The pattern detection device for biometric identification, which is discussed in the following paper, made use of mathematical modelling and descriptive statistics together with exploratory factor analysis i.e., Principal Component Analysis on the point of a function extraction technique. The proposed prestige gadget consisted of androgenic hair for the identification of biometric features with four hundred photographs for each database. A total of four-hundred pictures were gathered from each database. It was taken from a total of 25 respondents and sixteen snapshots from each respondent from hospitality industry. Performed with the highest accuracy, the system utilized a histogram equation with 2-fold cross-recognition, seventy-six. 68% of the average precision for the facial database and 19% mean accuracy for the androgenic hair database. Both means of accuracy are achieved using the 90 maximum large eigenvalues and their complementary eigenvectors within the principal component analysis attribute extraction technique.

Keywords

Neural Network, Fuzzy Control, Principal Component Analysis, Factor Analysis, Artificial Intelligence, Biometric, Hospitality Industry
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  • Biometric Face Recognition: Application of Neural Networks and Fuzzy Control in Hospitality Industry

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Authors

Harshit Sharma
B.Tech, Vellore Institute of Technology, Vellore, Tamil Nadu, India
Ashu Sharma
Associate Professor, School of Business Management, NMIMS University, Mumbai, Maharashtra, India
Dhruv Chouhan
B Tech, Vellore Institute of Technology, Vellore, Tamil Nadu, India

Abstract


The pattern detection device for biometric identification, which is discussed in the following paper, made use of mathematical modelling and descriptive statistics together with exploratory factor analysis i.e., Principal Component Analysis on the point of a function extraction technique. The proposed prestige gadget consisted of androgenic hair for the identification of biometric features with four hundred photographs for each database. A total of four-hundred pictures were gathered from each database. It was taken from a total of 25 respondents and sixteen snapshots from each respondent from hospitality industry. Performed with the highest accuracy, the system utilized a histogram equation with 2-fold cross-recognition, seventy-six. 68% of the average precision for the facial database and 19% mean accuracy for the androgenic hair database. Both means of accuracy are achieved using the 90 maximum large eigenvalues and their complementary eigenvectors within the principal component analysis attribute extraction technique.

Keywords


Neural Network, Fuzzy Control, Principal Component Analysis, Factor Analysis, Artificial Intelligence, Biometric, Hospitality Industry

References