Face Recognition By Using Neural Network
Somya Rastogi () and
Shivani Choudhary ()
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Somya Rastogi: Faculty of Information Management, Universiti Teknologi MARA (UiTM) Negeri Sembilan, Rembau Campus
Shivani Choudhary: Assistant Professor, Computer Science Department, Vidya College of Engineering, Meerut
Acta Informatica Malaysia (AIM), 2019, vol. 3, issue 2, 07-09
Now a day’s security is a big issue, the whole world has been working on the face recognition techniques as face is used for the extraction of facial features. An analysis has been done of the commonly used face recognition techniques. This paper presents a system for the recognition of face for identification and verification purposes by using Principal Component Analysis (PCA) with Back Propagation Neural Networks (BPNN) and the implementation of face recognition system is done by using neural network. The use of neural network is to produce an output pattern from input pattern. This system for facial recognition is implemented in MATLAB using neural networks toolbox. Back propagation Neural Network is multi-layered network in which weights are fixed but adjustment of weights can be done on the basis of sigmoidal function. This algorithm is a learning algorithm to train input and output data set. It also calculates how the error changes when weights are increased or decreased. This paper consists of background and future perspective of face recognition techniques and how these techniques can be improved.
Keywords: ANN; BPNN; NLP; PCA; Resilient Back propagation (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnaim:v:3:y:2019:i:2:p:07-09
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