Nibaran Das
Title
Cited by
Cited by
Year
A genetic algorithm based region sampling for selection of local features in handwritten digit recognition application
N Das, R Sarkar, S Basu, M Kundu, M Nasipuri, DK Basu
Applied Soft Computing 12 (5), 1592-1606, 2012
1272012
A statistical–topological feature combination for recognition of handwritten numerals
N Das, JM Reddy, R Sarkar, S Basu, M Kundu, M Nasipuri, DK Basu
Applied Soft Computing 12 (8), 2486-2495, 2012
1042012
A hierarchical approach to recognition of handwritten Bangla characters
S Basu, N Das, R Sarkar, M Kundu, M Nasipuri, DK Basu
Pattern Recognition 42 (7), 1467-1484, 2009
982009
CMATERdb1: a database of unconstrained handwritten Bangla and Bangla–English mixed script document image
R Sarkar, N Das, S Basu, M Kundu, M Nasipuri, DK Basu
International Journal on Document Analysis and Recognition (IJDAR) 15 (1), 71-83, 2012
922012
Handwritten Bangla Basic and Compound character recognition using MLP and SVM classifier
Nibaran Das, Brindaban Das, Ram Sarkar, Subhadip Basu, Mahantapas Kundu ...
Journal of Computing 2 (2), 2010
78*2010
A novel framework for automatic sorting of postal documents with multi-script address blocks
S Basu, N Das, R Sarkar, M Kundu, M Nasipuri, DK Basu
Pattern Recognition 43 (10), 3507-3521, 2010
75*2010
Handwritten Bangla alphabet recognition using an MLP based classifier
S Basu, N Das, R Sarkar, M Kundu, M Nasipuri, DK Basu
2nd National Conf. on Computer Processing of Bangla-2005, , Dhaka …, 2005
68*2005
A multi-objective approach towards cost effective isolated handwritten Bangla character and digit recognition
R Sarkhel, N Das, AK Saha, M Nasipuri
Pattern Recognition 58, 172-189, 2016
652016
Handwritten isolated Bangla compound character recognition: A new benchmark using a novel deep learning approach
S Roy, N Das, M Kundu, M Nasipuri
Pattern Recognition Letters 90, 15-21, 2017
642017
Handwritten Bangla Digit Recognition Using Classifier Combination Through DS Technique
S Basu, R Sarkar, N Das, M Kundu, M Nasipuri, DK Basu
International conference on pattern recognition and machine intelligence …, 2005
592005
Handwritten Bangla character recognition using a soft computing paradigm embedded in two pass approach
N Das, R Sarkar, S Basu, PK Saha, M Kundu, M Nasipuri
Pattern Recognition 48 (6), 2054-2071, 2015
532015
Word level script identification from Bangla and Devanagri handwritten texts mixed with Roman script
R Sarkar, N Das, S Basu, M Kundu, M Nasipuri, DK Basu
arXiv preprint arXiv:1002.4007, 2010
462010
PHDIndic_11: page-level handwritten document image dataset of 11 official Indic scripts for script identification
SM Obaidullah, C Halder, KC Santosh, N Das, K Roy
Multimedia Tools and Applications 77 (2), 1643-1678, 2018
422018
A multi-scale deep quad tree based feature extraction method for the recognition of isolated handwritten characters of popular indic scripts
R Sarkhel, N Das, A Das, M Kundu, M Nasipuri
Pattern Recognition 71, 78-93, 2017
422017
A benchmark image database of isolated Bangla handwritten compound characters
N Das, K Acharya, R Sarkar, S Basu, M Kundu, M Nasipuri
International Journal on Document Analysis and Recognition (IJDAR) 17 (4 …, 2014
402014
An MLP based Approach for Recognition of HandwrittenBangla'Numerals
S Basu, N Das, R Sarkar, M Kundu, M Nasipuri, DK Basu
arXiv preprint arXiv:1203.0876, 2012
402012
Text line segmentation for unconstrained handwritten document images using neighborhood connected component analysis
A Khandelwal, P Choudhury, R Sarkar, S Basu, M Nasipuri, N Das
International Conference on Pattern Recognition and Machine Intelligence …, 2009
392009
Understanding Deep Learning Techniques for Image Segmentation
S Ghosh, N Das, I Das, U Maulik
ACM Computing Survey, 2019
382019
An improved feature descriptor for recognition of handwritten Bangla alphabet
N Das, S Basu, R Sarkar, M Kundu, M Nasipuri
arXiv preprint arXiv:1501.05497, 2015
362015
The journey of graph kernels through two decades
S Ghosh, N Das, T Gonçalves, P Quaresma, M Kundu
Computer Science Review 27, 88-111, 2018
352018
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