most citedHandwritten Arabic Numeral Recognition using Deep Learning Neural Networks

8 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2017

An Efficient Single Chord-based Accumulation Technique (SCA) to Detect More Reliable Corners

Mohammad Asiful Hossain, Abdul Kawsar Tushar, Shofiullah Babor

Corner detection is a vital operation in numerous computer vision applications. The Chord-to-Point Distance Accumulation (CPDA) detector is recognized as the contour-based corner d…

cs.CV20171 cited

Reduction of Overfitting in Diabetes Prediction Using Deep Learning Neural Network

Akm Ashiquzzaman, Abdul Kawsar Tushar, Md. Rashedul Islam +1

Augmented accuracy in prediction of diabetes will open up new frontiers in health prognostics. Data overfitting is a performance-degrading issue in diabetes prognosis. In this stud…

cs.CV2017

A Novel Transfer Learning Approach upon Hindi, Arabic, and Bangla Numerals using Convolutional Neural Networks

Abdul Kawsar Tushar, Akm Ashiquzzaman, Afia Afrin +1

Increased accuracy in predictive models for handwritten character recognition will open up new frontiers for optical character recognition. Major drawbacks of predictive machine le…

cs.CV2017

Chord Angle Deviation using Tangent (CADT), an Efficient and Robust Contour-based Corner Detector

Mohammad Asiful Hossain, Abdul Kawsar Tushar

Detection of corner is the most essential process in a large number of computer vision and image processing applications. We have mentioned a number of popular contour-based corner…

cs.CV20178 cited

Handwritten Arabic Numeral Recognition using Deep Learning Neural Networks

Akm Ashiquzzaman, Abdul Kawsar Tushar

Handwritten character recognition is an active area of research with applications in numerous fields. Past and recent works in this field have concentrated on various languages. Ar…