The efficient transmission of variable-bit-rate (VBR) video streams is complicated by the burstiness that video compression standards such as MPEG introduce. Most of the existing techniques concentrate on stored video traffic smoothing or real-time video traffic smoothing. However, there is a growing number of live video applications, such as video-casts of courses or television news, where man...

Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on the policies of the other agents. This creates a situation of learning a moving target. Previous learning algorithms have one of two shortcomings depending on their approach. They either converge to a policy that may n...

Bezier curves (BC) are important tools in a wide range of diverse and challenging applications, from computer aided design to generic object shape descriptors. A major constraint of the classical BC is that only global information concerning control points (CP) is considered, consequently there may be a sizeable gap between the BC and its control polygon (CtrlPoly), leading to a large distortio...

Recently, vision transformers have been applied in many computer problems due to its long-range learning ability. However, it has not throughly explored image compression. We propose a patch-based learned compression network by incorporating transformers. The input is divided into patches before feeding the encoder and are reconstructed from decoder form complete image. Different kinds of trans...

This paper presents two techniques for variable rate speech coding using wavelet representations. In the rst method, the Daubechies wavelet is used to produce a wavelet representation of the speech signal. This representation is encoded using some of the properties of the speech signal to allocate bits to the various subbands. A technique to lower the bit rate using vector quantisation is discu...