DocumentCode
3252520
Title
Data compression for image recognition using neural network
Author
Liu, Jun ; Wang, Danwei
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
Volume
4
fYear
1992
fDate
7-11 Jun 1992
Firstpage
333
Abstract
The authors present some preliminary results on the performance of image compression and decompression using a counterpropagation neural network. The counterpropagation network is a combination of two kinds of algorithms, i.e., Kohonen´s self-organizing map and Grossberg´s outstar. The training methods, compression procedures, and recovering procedures are discussed. Examples are presented to demonstrate the network training and image transmission
Keywords
data compression; image recognition; neural nets; self-organising feature maps; compression procedures; counterpropagation network; counterpropagation neural network; image compression; image decompression; image recognition; image transmission; neural network; outstar; recovering procedures; self-organizing map; training methods; Backpropagation; Data compression; Image coding; Image communication; Image recognition; Neural networks; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227321
Filename
227321
Link To Document