We address the problem of single image super-resolution by exploring the manifold properties. Given a set of low resolution image patches and their corresponding high resolution patches, we assume they respectively reside on two non-linear manifolds that have similar locallylinear structure. This manifold correlation can be realized by a threelayer Markov network that connects performing super-...

The Peer-to-Peer (P2P) computing model has recently been recognized as a more natural and flexible approach to sharing resources. However, a fundamental issue, content locating (or content search) in P2P-based applications has not yet been successfully resolved. This thesis documents the design and implementation of a novel architecture, which combines the advantages of cluster infrastructure a...

In recent years, deep learning methods have been successfully applied to single-image super-resolution tasks. Despite their great performances, deep learning methods cannot be easily applied to real-world applications due to the requirement of heavy computation. In this paper, we address this issue by proposing an accurate and lightweight deep learning model for image super-resolution. In detai...