@article{(Open Science Index):https://publications.waset.org/pdf/15671,
	  title     = {Integrating Low and High Level Object Recognition Steps by Probabilistic Networks},
	  author    = {András Barta and  István Vajk},
	  country	= {},
	  institution	= {},
	  abstract     = {In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {7},
	  year      = {2007},
	  pages     = {2113 - 2122},
	  ee        = {https://publications.waset.org/pdf/15671},
	  url   	= {https://publications.waset.org/vol/7},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 7, 2007},