Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2403
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMohapatra, R K-
dc.contributor.authorMajhi, B-
dc.contributor.authorJena, S K-
dc.date.accessioned2015-12-16T12:39:38Z-
dc.date.available2015-12-16T12:39:38Z-
dc.date.issued2015-12-
dc.identifier.citationInternational Conference on Computing, Communication and Security (ICCCS-2015) , Pamplemousses, Mauritius, 4-6 December, 2015en_US
dc.identifier.urihttp://hdl.handle.net/2080/2403-
dc.descriptionCopyright for this paper belongs to proceeding publisheren_US
dc.description.abstractHere, we propose a method for recognition of handwritten English digit utilizing discrete cosine space-frequency transform known as the Discrete Cosine S-Transform (DCST). Experiments have been conducted on the publicly available standard MNIST handwritten digit database. The DCST features along with an Artificial Neural Network (ANN) classifier is utilized for solving the classification issues of written by hand digit. The Discrete Cosine S-Transform coefficients are extracted from the standard images of MNIST handwritten isolated digit database. The database consists of a total of 70000 including 60000 training samples and 10000 test samples. To overcome the computational overhead, we have normalized all the images of the MNIST dataset from 28 28 to 20 20 image size by eliminating the unsought boundary pixels up to width four. Further, the classification of digits has been made by using a back propagation neural network (BPNN). This work has achieved precisely 98.8% of success rate for MNIST database.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectClassificationen_US
dc.subjectMNIST dataseten_US
dc.subjectDiscrete Cosine STransformen_US
dc.subjectBPNNen_US
dc.titleClassification Performance Analysis of MNIST Dataset Utilizing A Multi-Resolution Techniqueen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
Classification_Mohapatra_2015.pdf354.45 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.