Title :
A Co-evolutionary Competitive Multi-expert Approach to Image Compression with Neural Networks
Author :
Fard, Mahdi Milani
Author_Institution :
Fac. of Eng., Tehran Univ.
Abstract :
Bottle-neck MLP neural networks have been used in image compression and a few methods are developed to increase the compression quality. In this paper, a new co-evolutionary method is proposed to further improve the compression efficiency. A heterogeneous set of networks co-evolve and compete to compress different parts of an image with different characteristics. The results indicate a great improvement over the non-evolving methods
Keywords :
data compression; expert systems; image coding; neural nets; coevolutionary competitive multiexpert approach; image compression; neural network; nonevolving method; Computer networks; Data preprocessing; Feeds; Image coding; Neural networks; Neurons; Pixel; Sampling methods; Shape; Tiles; Co-evolution; Image compression; Multi-expert; Neural Networks;
Conference_Titel :
Engineering of Intelligent Systems, 2006 IEEE International Conference on
Conference_Location :
Islamabad
Print_ISBN :
1-4244-0456-8
DOI :
10.1109/ICEIS.2006.1703150
