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dc.contributor.authorThornton, John
dc.contributor.authorSrbic, Andrew
dc.contributor.authorMain, Linda
dc.contributor.authorChitsaz, Mahsa
dc.contributor.editorD. Wang and M. Reynolds
dc.date.accessioned2017-05-03T12:54:37Z
dc.date.available2017-05-03T12:54:37Z
dc.date.issued2011
dc.date.modified2012-07-22T22:51:06Z
dc.identifier.issn03029743
dc.identifier.doi10.1007/978-3-642-25832-9_27
dc.identifier.urihttp://hdl.handle.net/10072/43965
dc.description.abstractIt is a widely held view in contemporary computational neuroscience that the brain responds to sensory input by producing sparse distributed representations. In this paper we investigate a brain-inspired spatial pooling algorithm that produces such sparse distributed representations by modelling the formation of proximal dendrites associated with neocortical minicolumns. In this approach, distributed representations are formed out of a competitive process of inter-column inhibition and subsequent learning. Specifically, we evaluate the performance of a recently proposed binary spatial pooling algorithm on a well-known benchmark of greyscale natural images. Our main contribution is to augment the algorithm to handle greyscale images, and to produce better quality encodings of binary images. We also show that the augmented algorithm produces superior population and lifetime kurtosis measures in comparison to a number of other well-known coding schemes.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent154125 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom261
dc.relation.ispartofpageto270
dc.relation.ispartofjournalLecture Notes in Computer science
dc.relation.ispartofvolume7106
dc.rights.retentionY
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classified
dc.subject.fieldofresearchcode080199
dc.titleAugmented Spatial Pooling
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2011 Springer Berlin / Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com
gro.date.issued2011
gro.hasfulltextFull Text
gro.griffith.authorThornton, John R.
gro.griffith.authorMain, Linda M.
gro.griffith.authorSrbic, Andrew
gro.griffith.authorChitsaz, Mahsa


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