@article{(Open Science Index):https://publications.waset.org/pdf/3357,
	  title     = {A Fast Adaptive Content-based Retrieval System of Satellite Images Database using Relevance Feedback},
	  author    = {Hanan Mahmoud Ezzat Mahmoud and  Alaa Abd El Fatah Hefnawy},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, we present a system for content-based
retrieval of large database of classified satellite images, based on
user's relevance feedback (RF).Through our proposed system, we
divide each satellite image scene into small subimages, which stored
in the database. The modified radial basis functions neural network
has important role in clustering the subimages of database according
to the Euclidean distance between the query feature vector and the
other subimages feature vectors. The advantage of using RF
technique in such queries is demonstrated by analyzing the database
retrieval results.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {7},
	  year      = {2008},
	  pages     = {2419 - 2423},
	  ee        = {https://publications.waset.org/pdf/3357},
	  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},
	}