Title :
Input data clustering to improve neural network performance
Author :
Su, Min ; Basu, Mitra
Author_Institution :
Dept. of Electr. Eng., City Univ. of New York, NY, USA
Abstract :
We focus on the pre-processing of the training data. We find that when a network is trained with selected input, the performance of the network improves significantly as opposed to a network that does not receive selected input data for training. Furthermore, less time is required to train such networks. The problem of image deblurring is used to test the performance of such a network
Keywords :
image restoration; learning (artificial intelligence); neural nets; pattern clustering; image deblurring; input data clustering; learning; network performance; neural network; Artificial neural networks; Cities and towns; Educational institutions; Image restoration; Neural networks; Optical computing; Optical imaging; Speech recognition; Testing; Training data;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939010
