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dc.contributor.authorGe, ZongYuan
dc.contributor.authorBewley, Alex
dc.contributor.authorMcCool, Christopher
dc.contributor.authorCorke, Peter
dc.contributor.authorUpcroft, Ben
dc.contributor.authorSanderson, Conrad
dc.date.accessioned2020-07-30T01:48:52Z
dc.date.available2020-07-30T01:48:52Z
dc.date.issued2016
dc.identifier.doi10.1109/wacv.2016.7477700
dc.identifier.urihttp://hdl.handle.net/10072/395908
dc.description.abstractWe present a novel deep convolutional neural network (DCNN) system for fine-grained image classification, called a mixture of DCNNs (MixDCNN). The fine-grained image classification problem is characterised by large intra-class variations and small inter-class variations. To overcome these problems our proposed MixDCNN system partitions images into K subsets of similar images and learns an expert DCNN for each subset. The output from each of the K DCNNs is combined to form a single classification decision. In contrast to previous techniques, we provide a formulation to perform joint end-to-end training of the K DCNNs simultaneously. Extensive experiments, on three datasets using two network structures (AlexNet and GoogLeNet), show that the proposed MixDCNN system consistently outperforms other methods. It provides a relative improvement of 12.7% and achieves state-of-the-art results on two datasets.
dc.description.peerreviewedYes
dc.publisherIEEE
dc.relation.ispartofconferencenameIEEE Winter Conference on Applications of Computer Vision (WACV 2016)
dc.relation.ispartofconferencetitle2016 IEEE Winter Conference on Applications of Computer Vision (WACV)
dc.relation.ispartofdatefrom2016-03-07
dc.relation.ispartofdateto2016-03-10
dc.relation.ispartoflocationLake Placid, USA
dc.subject.fieldofresearchImage Processing
dc.subject.fieldofresearchComputer Vision
dc.subject.fieldofresearchcode080106
dc.subject.fieldofresearchcode080104
dc.titleFine-grained classification via mixture of deep convolutional neural networks
dc.typeConference output
dc.type.descriptionE1 - Conferences
dcterms.bibliographicCitationGe, Z; Bewley, A; McCool, C; Corke, P; Upcroft, B; Sanderson, C, Fine-grained classification via mixture of deep convolutional neural networks, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 2016
dc.date.updated2020-07-29T04:30:41Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorSanderson, Conrad


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