Title :
Districted matching approach for 1D object classification
Author :
Chen, Liang ; Nilufar, Sharmin ; Kwan, H.K.
Author_Institution :
Comput. Sci. Dept., Univ. of Northern British Columbia, Prince George, BC, Canada
Abstract :
This paper proves that the districted matching scheme is more stable than undistricted matching scheme for pattern classification applications, where an object to be classified consists of elements lying on a limited line segment in 1D space. The theoretical result suggests the using of districted matching schemes for pattern recognition/recognition of 1D objects. The method is used in the predication of start codons of nucleotide sequences by artificial neural network based approaches.
Keywords :
biology computing; learning (artificial intelligence); neural nets; object recognition; pattern classification; sequences; 1D object classification; 1D object recognition; artificial neural network; districted matching; limited line segment; nucleotide sequences; pattern classification; pattern recognition; start codons; supervised machine learning; Application software; Artificial neural networks; Computer science; Feature extraction; Neural networks; Pattern classification; Pattern matching; Pattern recognition; Pollution; Voting;
Conference_Titel :
Intelligent Multimedia, Video and Speech Processing, 2004. Proceedings of 2004 International Symposium on
Print_ISBN :
0-7803-8687-6
DOI :
10.1109/ISIMP.2004.1434036
