In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …

Deep learning architectures are now pervasive and filled almost all applications under
image processing, computer vision, and biometrics. The attractive property of feature …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

We review a class of methods that can be collected under the name nonlinear transform
coding (NTC), which over the past few years have become competitive with the best linear …

Traditional video compression approaches build upon the hybrid coding framework with
motion-compensated prediction and residual transform coding. In this paper, we propose the …

Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Deep learning methods are increasingly being applied in the optimisation of video
compression algorithms and can achieve significantly enhanced coding gains, compared to …

Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …

In the 17 years since the first edition of Fundamentals of Multimedia, the field and
applications of multimedia have flourished and are undergoing evermore rapid growth and …

Metaverse, a set of fully immersive digital worlds where people can interact with one another
using three-dimensional (3-D) avatars, is poised to become an increasingly popular …