The capability of multi column convolutional networks in identifying local invariant features
helps improve its performance on image classification tasks to a large extent. Suppression of …

The pandemic of Covid-19 has caused a shift of paradigm of education, from face-to-face to
e-learning. E-learning leads to an escalation in digitalization of handwritten documents …

Background: The data proliferation has been resulted in large-scale, high dimensional data
and brings new challenges for feature selection in handwriting recognition problems. The …

The character recognition technique is based on electronic or mechanical transformation of
handwritten or printed document images into machine interpretable form. The machine …

In this paper we introduce a real Pashtu handwritten numerals dataset (PHND) having
50,000 scanned images and make publicly available for research and scientific use …

Convolutional neural network (CNN) based methods have succeeded for handwritten
numeral recognition (HNR) applications. However, CNN seems to misclassify similarly …

This paper presents a publicly accessible Bangla offline handwriting dataset, as well as
benchmarking with a simple and robust isolated handwritten character recognition scheme …

This work presents an Xception ensemble network based Bangla handwritten digit
classification scheme. Bangla handwritten digits are challenging to recognize due to some …

Handwritten character recognition has become a challenging and interesting field in the
recent days due to its complex character shapes and huge pragmatic applications. A lot of …

The traditional ML development methodology does not enable a large number of
contributors, each with distinct objectives, to work collectively on the creation and extension …