@article{(Open Science Index):https://publications.waset.org/pdf/3993,
	  title     = {Finding Sparse Features in Face Detection Using Genetic Algorithms},
	  author    = {H. Sagha and  S. Kasaei and  E. Enayati and  M. Dehghani},
	  country	= {},
	  institution	= {},
	  abstract     = {Although Face detection is not a recent activity in the
field of image processing, it is still an open area for research. The
greatest step in this field is the work reported by Viola and its recent
analogous is Huang et al. Both of them use similar features and also
similar training process. The former is just for detecting upright
faces, but the latter can detect multi-view faces in still grayscale
images using new features called 'sparse feature'. Finding these
features is very time consuming and inefficient by proposed methods.
Here, we propose a new approach for finding sparse features using a
genetic algorithm system. This method requires less computational
cost and gets more effective features in learning process for face
detection that causes more accuracy.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {7},
	  year      = {2008},
	  pages     = {2337 - 2340},
	  ee        = {https://publications.waset.org/pdf/3993},
	  url   	= {https://publications.waset.org/vol/19},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 19, 2008},