DocumentCode
3329606
Title
Learning and recognition of similar temporal sequences
Author
Fujii, Robert H. ; Hayashi, Taiichiro
Author_Institution
Univ. of Aizu, Aizu Wakamatsu, Japan
fYear
2009
fDate
2-5 Aug. 2009
Firstpage
885
Lastpage
888
Abstract
Learning and recognition of object velocity sequences using a hierarchical network similar in structure to the mammalian neocortex is proposed. Space and time invariant representations of velocity sequences are captured in an unsupervised manner. Recognition of similar sequences are achieved by allowing some variance in the learned velocity vectors.
Keywords
image motion analysis; medical image processing; object recognition; unsupervised learning; hierarchical network similar; mammalian neocortex; object recognition; similar temporal sequences; space invariant representations; time invariant representations; velocity sequences; Animal structures; Cities and towns; Feedforward neural networks; Neural networks; Neurofeedback; Object recognition; Output feedback; Proposals; Shape; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2009. MWSCAS '09. 52nd IEEE International Midwest Symposium on
Conference_Location
Cancun
ISSN
1548-3746
Print_ISBN
978-1-4244-4479-3
Electronic_ISBN
1548-3746
Type
conf
DOI
10.1109/MWSCAS.2009.5235908
Filename
5235908
Link To Document