DocumentCode :
2185721
Title :
Stable third-order tensor representation for colour image classification
Author :
Tao, Dacheng ; Maybank, Steve ; Hu, Weiming ; Li, Xuelong
Author_Institution :
Sch. of Comput. Sci. & Inf. Syst., London Univ., UK
fYear :
2005
fDate :
19-22 Sept. 2005
Firstpage :
641
Lastpage :
644
Abstract :
General tensors can represent colour images more naturally than conventional features; however, the general tensors´ stability properties are not reported and remain to be a key problem. In this paper, we use the tensor minimax probability (TMPM) to prove that the tensor representation is stable. The proof is based on the random subspace method through a large number of experiments.
Keywords :
image classification; image colour analysis; minimax techniques; probability; tensors; colour image classification; random subspace; stable third-order tensor representation; tensor minimax probability; Color; Computational complexity; Covariance matrix; Humans; Kernel; Learning systems; Machine learning; Machine learning algorithms; Minimax techniques; Tensile stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2415-X
Type :
conf
DOI :
10.1109/WI.2005.136
Filename :
1517925
Link To Document :
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