1. DSpaceCRIS@UNITEN
  2. College of Engineering
  3. COE Scholarly Publication
Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/6977
DC FieldValueLanguage
dc.contributor.authorHu, Y.en_US
dc.contributor.authorNeoh, D.T.H.en_US
dc.contributor.authorSahari, K.S.M.en_US
dc.contributor.authorLoo, C.K.en_US
dc.date.accessioned2018-01-11T08:27:41Z-
dc.date.available2018-01-11T08:27:41Z-
dc.date.issued2014-
dc.description.abstractThis article introduced an improved spatio - temporal deep network based on information filter method for learning sufficient representation. The proposed method aims to improve feature learning capability while modeling spatial and temporal dependencies. Experiments on pattern recognition are conducted to validate the effectiveness of the proposed method. © 2014 IEEE.
dc.language.isoenen_US
dc.titleLearning sufficient representation for spatio-temporal deep network using information filteren_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/SII.2014.7028116-
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:COE Scholarly Publication
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