Abstract Internet of Things (IoT) systems cannot successfully realize the notion of ubiquitous
connectivity of everything if they are not capable to truly include 'multimedia things' …

Compressed sensing (CS) has emerged as a promising technique to jointly sense and
compress sparse signals. One of the most promising applications of CS is compressive …

Recently, deep learning-based compressed sensing (CS) has achieved great success in
reducing the sampling and computational cost of sensing systems and improving the …

For compressed sensing (CS) recovery, the reconstruction quality is highly dependent on
the sparsity level of the representation for the signal. Motivated by the observation that the …

Distributed compressive video sensing (DCVS) has great potential for signal acquisition and
processing in source-limited communication, eg, wireless video sensors networks, because …

Compressed Sensing, an emerging framework for signal processing, can be used in image
and video application, especially when available resources at the transmitter side are …

Wireless multimedia sensor networks (WMSNs) have been used for sensitive applications
such as video surveillance and monitoring applications. In a WMSN, storage and …

Deep image prior (DIP) is an emerging technology that indicates that the structure of an
untrained network can serve as an excellent prior for image restoration. It bridges the gap …

The standard compressive sensing (CS) theory can be improved for robust recovery with
fewer measurements under the assumption that signals lie on a union of subspaces (UoS) …

In this paper, we propose a cascaded sparse/DCT (S/DCT) two-layer representation of
prediction residuals, and implement this idea on top of the state-of-the-art high efficiency …