Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to
support disruptive applications such as extended reality (XR), augmented/virtual reality …

Due to recent advances in digital technologies, and availability of credible data, an area of
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …

Convolutional neural networks (CNNs) have been applied to visual tasks since the late
1980s. However, despite a few scattered applications, they were dormant until the mid …

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized
computer vision through end‐to‐end learning, that is, learning from the raw data. There is …

Artificial intelligence (AI) and machine learning (ML) tools play a significant role in the recent
evolution of smart systems. AI solutions are pushing towards a significant shift in many fields …

Intelligent tasks, such as visual perception, auditory perception, and language
understanding require the construction of good internal representations of the world (or" …

Deep Neural Networks now excel at image classification, detection and segmentation. When
used to scan images by means of a sliding window, however, their high computational …

Event-driven visual sensors have attracted interest from a number of different research
communities. They provide visual information in quite a different way from conventional …

Convolutional neural networks (CNN) applications range from recognition and reasoning
(such as handwriting recognition, facial expression recognition and video surveillance) to …

We present a technique for learning a manifold of human motion data using Convolutional
Autoencoders. Our approach is capable of learning a manifold on the complete CMU …