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dc.contributor.authorVo, Trung Hieu-
dc.contributor.authorPhan, Thi Kim Chi-
dc.contributor.authorVo, Hong Phuc Hanh-
dc.contributor.authorTran, Dinh Kha-
dc.contributor.authorDo, Trong Hop-
dc.descriptionThe 11th Conference on Information Technology and its Applications; Topic: Image and Natural Language Processing; pp.165-172.vi_VN
dc.description.abstractThe data for deep learning is growing bigger day by day. That leads to traditional processing systems facing computing resource limitations. So, distributed parallel computing system for training deep learing models is needed. Within the scope of this paprer, we deploy some traditional deep learning models such as Lenet and Alexnet for Vietnamese food image classification. Model performance is relatively satisfactory, with an accuracy of 49% with Lenet. Details of the data processing and model architecture are explained in the sections below.vi_VN
dc.publisherDa Nang Publishing Housevi_VN
dc.subjectDeep Learningvi_VN
dc.subjectBig Datavi_VN
dc.subjectDistributed and parallel computingvi_VN
dc.subjectImage classificationvi_VN
dc.subjectVietnamese foodvi_VN
dc.titleVietnamese Food Image Classification Using Distributed Deep Learningvi_VN
dc.typeWorking Papervi_VN
Appears in Collections:CITA 2022

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