Robust learning in adaptive processing of data structures for tree representation based image classification

Author

Cho, Siu-Yeung ; Chi, Zheru ; Wang, Zhiyong ; Siu, Wan-chi

Author_Institution

Centre for Multimedia Signal Process., Hong Kong Polytech. Univ., Kowloon, China

Volume

2

fYear

2002

fDate

2002

Firstpage

108

Abstract

In this paper, novel robust learning in adaptive processing of data structures for tree representation based image classification is proposed. The idea of this learning scheme is to optimize the free parameters of the node representation in data structures by using the layer-by-layer least squares method. The vanishing gradient information can be recovered to overcome the learning long-term dependency problem for this adaptive processing.

Keywords

adaptive signal processing; backpropagation; image classification; least squares approximations; natural scenes; neural nets; quadtrees; backpropagation through structure algorithm; data structure adaptive processing; free parameter optimization; layer-by-layer least squares method; learning scheme; live plant images; natural scene images; node representation; quad-tree structure; robust learning; single-hidden-layer neural network; tree representation based image classification; vanishing gradient information; Adaptive signal processing; Backpropagation algorithms; Convergence; Data structures; Image classification; Neural networks; Pixel; Robustness; Tree data structures; Tree graphs;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2002. Proceedings. 16th International Conference on

ISSN

1051-4651

Print_ISBN

0-7695-1695-X

Type

conf

DOI

10.1109/ICPR.2002.1048249

Filename

1048249