Over the past few years, the computer vision domain has evolved and made a revolutionary
transition from human-engineered features to automated features to address challenging …

Classifying digital images using neural networks is one of the most fundamental tasks within
the field of artificial intelligence. For a long time, convolutional neural networks have proven …

Numerous advancements in various fields, including pattern recognition and image
classification, have been made thanks to modern computer vision and machine learning …

Capsule networks have been shown to be powerful models for image classification, thanks
to their ability to represent and capture viewpoint variations of an object. However, the high …

Convolutional neural networks (CNNs) have achieved human-level performance in various
computer vision tasks, such as image classification, object detection & segmentation, etc …

Modern day computer vision tasks requires efficient solution to problems such as image
recognition, natural language processing, object detection, object segmentation and …

Modern day computer vision tasks requires efficient solution to problems such as image
recognition, natural language processing, object detection, object segmentation and …

In recent years, convolutional neural networks (CNN) have played an important role in the
field of deep learning. Variants of CNN's have proven to be very successful in classification …

Capsule networks use routing algorithms to flow information between consecutive layers. In
the existing routing procedures, capsules produce predictions (termed votes) for capsules of …

Capsule network is a new network structure which can encode the properties and spatial
relations of image features. It overcomes the shortcomings of CNN that requiring large …