most citedHandwritten Bangla Basic and Compound character recognition using MLP and SVM classifier

81 citations · 147 across the 6 of their papers we have counts for

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cs.CV20104 cited

A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron

Nibaran Das, Ayatullah Faruk Mollah, Ram Sarkar +1

The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The…

cs.CV201027 cited

Handwritten Arabic Numeral Recognition using a Multi Layer Perceptron

Nibaran Das, Ayatullah Faruk Mollah, Sudip Saha +1

Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the pr…

cs.CV20106 cited

Text Region Extraction from Business Card Images for Mobile Devices

Ayatullah Faruk Mollah, Subhadip Basu, Nibaran Das +3

Designing a Business Card Reader (BCR) for mobile devices is a challenge to the researchers because of huge deformation in acquired images, multiplicity in nature of the business c…

cs.CV20104 cited

Binarizing Business Card Images for Mobile Devices

Ayatullah Faruk Mollah, Subhadip Basu, Nibaran Das +3

Business card images are of multiple natures as these often contain graphics, pictures and texts of various fonts and sizes both in background and foreground. So, the conventional…

cs.CV201081 cited

Handwritten Bangla Basic and Compound character recognition using MLP and SVM classifier

Nibaran Das, Bindaban Das, Ram Sarkar +3

A novel approach for recognition of handwritten compound Bangla characters, along with the Basic characters of Bangla alphabet, is presented here. Compared to English like Roman sc…