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 …

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 …

The advancement in the machine learning and the computer vision has caused several
improvements and development in numerous of domains. Capsule neural networks are one …

Past few years have witnessed exponential growth of interest in deep learning
methodologies with rapidly improving accuracies and reduced computational complexity. In …

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 …

In capsule networks, the routing algorithm connects capsules in consecutive layers,
enabling the upper-level capsules to learn higher-level concepts by combining the concepts …

Deep convolutional neural networks, assisted by architectural design strategies, make
extensive use of data augmentation techniques and layers with a high number of feature …

Most capsule network designs rely on traditional matrix multiplication between capsule
layers and computationally expensive routing mechanisms to deal with the capsule …

Capsule Network (CapsNet) is a methodology with good prospects in visual tasks, since it
can keep a stronger relationship of spatial information than Convolutional Neural Networks …