Face recognition using combined binary particle swarm optimisation and hidden layer of artificial neural network
by S.G. Charan
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 14, No. 1/2, 2019

Abstract: Face recognition is one of the challenging domains. We have seen artificial neural network perform very well in both detection and recognition. In this paper, we propose a novel method of feature extraction where features obtained at the end of hidden layer of neural network is utilised. This hidden layer output is our first level of features. On these features, we apply binary particle swarm optimisation (BPSO) to remove the redundancy, the few hidden units in the network. BPSO over hidden layer outputs can be implemented in two ways: 1) to apply BPSO over hidden layer in the training stage so the network is better optimised; 2) to directly use the BPSO on an optimised neural network's hidden layer output. Both the techniques performed well over traditional neural network and conventional BPSO. Experiments on FERET and LFW datasets show promising results.

Online publication date: Mon, 14-Oct-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com