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

The ubiquitous camera networks in the city brain system grow at a rapid pace, creating
massive amounts of images and videos at a range of spatial-temporal scales and thereby …

Thousands of videos are posted on websites and social media every day, including Twitter,
Facebook, WhatsApp, Instagram, and YouTube. Newspapers, law enforcement publications …

Wasserstein generative adversarial network (WGAN) has attracted great attention due to its
solid mathematical background, ie, to minimize the Wasserstein distance between the …

Neural video compression has recently demonstrated significant potential to compete with
conventional video codecs in terms of rate-quality performance. These learned video codecs …

Neural Network (NN)-based coding techniques are being developed for hybrid video coding
schemes, such as the Versatile Video Coding (VVC) standard. In-loop filters and …

Deep learning is now playing an important role in enhancing the performance of
conventional hybrid video codecs. These learning-based methods typically require diverse …

We propose a new Generative Adversarial Network for Compressed Video frame quality
Enhancement (CVEGAN). The CVEGAN generator benefits from the use of a novel Mul 2 …

With recent advances in deep learning, numerous algorithms have been developed to
enhance video quality, reduce visual artifacts, and improve perceptual quality. However …

A novel active and collaborative learning approach that uses videos to enhance student
participation and motivation in Electrical Engineering courses at the University of Málaga, is …