DocumentCode
1749049
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
Volume
1
fYear
2001
fDate
2001
Firstpage
160
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.939010
Filename
939010
Link To Document