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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15659
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dc.contributor.authorKeserwani P.-
dc.contributor.authorAli T.-
dc.contributor.authorPratim Roy, Partha-
dc.date.accessioned2020-12-02T11:41:29Z-
dc.date.available2020-12-02T11:41:29Z-
dc.date.issued2018-
dc.identifier.citationProceedings of 2017 9th International Conference on Advances in Pattern Recognition, ICAPR 2017, (2018), 70- 75-
dc.identifier.isbn9.78154E+12-
dc.identifier.urihttps://doi.org/10.1109/ICAPR.2017.8592983-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/15659-
dc.description.abstractRecognizing Bangla compound characters is a challenging problem due to its high curly nature. In this paper, we propose a convolutional neural network (CNN) architecture to recognize handwritten Bangla compound characters. The learning of proposed architecture is done in two phase. In the first phase, a CNN is trained in an unsupervised way to minimize the reconstruction loss. Afterward, these weights are used to initialize the starting layers of second CNN to reduce the recognition loss through supervised learning. The effectiveness of the proposed model is validated on compound character dataset CMATERdb 3.1.3.3, which consists of 171 different character classes. It achieves recognition results of 93.90% and 97.37 % in top 1 and top 2 choices. The recognition performance outperforms state-of-the-art method for handwritten Bangla compound characters by a margin of 3.57%. © 2017 IEEE.-
dc.language.isoen_US-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.relation.ispartofProceedings of 2017 9th International Conference on Advances in Pattern Recognition, ICAPR 2017-
dc.subjectCompound character-
dc.subjectConvolutional Neural Network-
dc.subjectHandwritten Bangla character recognition-
dc.titleA two phase trained Convolutional Neural Network for Handwritten Bangla Compound Character Recognition-
dc.typeConference Paper-
dc.scopusid57205562856-
dc.scopusid55314607400-
dc.scopusid56880478500-
dc.affiliationKeserwani, P., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India-
dc.affiliationAli, T., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India-
dc.affiliationRoy, P.P., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India-
dc.identifier.conferencedetails9th International Conference on Advances in Pattern Recognition, ICAPR 2017, 27-30 december 2017-
Appears in Collections:Conference Publications [CS]

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