Research on intelligent wireless network aims at the development of a human society which
is ubiquitous and mobile, simultaneously providing solutions to the coverage, capacity, and …

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 …

Most data is automatically collected and only ever" seen" by algorithms. Yet, data
compressors preserve perceptual fidelity rather than just the information needed by …

There has been much interest in deploying deep learning algorithms on low-powered
devices, including smartphones, drones, and medical sensors. However, full-scale deep …

Abstract Image Coding for Machines (ICM) aims to compress images for AI tasks analysis
rather than meeting human perception. Learning a kind of feature that is both general (for AI …

An increasing share of image and video content is analyzed by machines rather than viewed
by humans, and therefore it becomes relevant to optimize codecs for such applications …

Most video compression methods aim to improve the decoded video visual quality, instead
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …

Lossy image compression aims to represent images in as few bits as possible while
maintaining fidelity to the original. Theoretical results indicate that optimizing distortion …

The past decade has witnessed the rising dominance of deep learning and artificial
intelligence in a wide range of applications. In particular, the ocean of wireless smartphones …