International Journal of Science, Engineering and Computer Technology

Jyoti Goyat ¹, Sakshi Dhingra ¹, Vinod Goyal ¹

Affiliations
1 Guru Jambeshwar University Science and Technology, Hisar, Haryana, IN

Abstract

This paper provides an overview on face recognition and its various techniques. As in this enviromnent importance of security is increasing. So for organization identification and authentication is also important. Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification in a wide range of apphcations like identity authentication, smart cards, security access control, surveillance and intelligent human computer interaction. Such requirement for reliable personal identification in computerized access control has resulted in an increased in bio-metrics and in the main field the face recognition. Face recognition is a bio-metric method of identifying a person based on a photograph of his face. There are different kinds of algorithms for the face recognition. Also different types of databases are available for face recognition like ORL, FERET, Asian and Korean etc.

Keywords

Face Recognition, Techniques.

Full Text

     

Jyoti Goyat ¹, Sakshi Dhingra ¹, Vinod Goyal ¹

Affiliations
1 Guru Jambeshwar University Science and Technology, Hisar, Haryana, IN

Abstract

Neural networks have emerged as advanced data mining tools in cases where other techniques may not produce satisfactory predictive models. As the term implies, neural networks have a biologically inspired modelling capability but are essentially statistical modelling tools. Artificial neural networks is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. Artificial Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques that could help in Decision-making .Neural Networks have been successfully applied in a wide range of supervised and unsupervised learning applications. ANN methods are not commonly used for data-mining tasks, because they may have complex structure,long training time, and uneasily understandable representation of results& often produce incomprehensible models. However, artificial neural networks have high acceptance ability for noisy data and high accuracy and are preferable in data mining.

Keywords

Artificial Neural Network (ann), Neural Network Topology Data Mining, Data Warehousing.

Full Text