This paper summarizes the top state-of-the-art contributions reported on the MNIST dataset
for handwritten digit recognition. This dataset has been extensively used to validate novel …

Neural networks have made big strides in image classification. Convolutional neural
networks (CNN) work successfully to run neural networks on direct images. Handwritten …

Optical Character recognition is an eminent topic of research in modern times. An
exhaustive research is going on character recognition of different languages. These …

In this study, we design an interface optimized for the platform by adopting deep learning in
an asymmetric virtual environment where virtual reality (VR) and augmented reality (AR) …

Cerebral palsy (CP) is used to describe a group of disorders, characterized by non-
progressive, but permanent damage to the developing brain that results in motor deficits …

Convolutional neural networks (CNN) have transformed the field of computer vision by
enabling the automatic extraction of features, obviating the need for manual feature …

This paper proposes a novel text interface using deep learning in a mobile platform
environment and presents the English language teaching applications created based on our …

Hand gestures, whether static or dynamic, are a field of intense study and have several
potential uses for human-computer interaction in real-time systems. Static and dynamic hand …

In this paper a detailed review of Handwritten Character Recognition is presented. Some
features of human beings are unique to individuals like iris, fingerprint, DNA etc. Handwriting …

Developing systems in the computer vision domain persuade researchers in many
applications. The main goal in computer vision applications is to enable the computers to …