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To improve the parallel processing capability of video coding, the emerging high efficiency video coding (HEVC) standard introduces two parallel techniques, i.e., Wavefront Parallel Processing (WPP) and Tiles , to make it much more parallel-friendly than its predecessors. However, these two techniques are designed to explore coarse-grained parallelism in HEVC encoding on multicore Central Processing Unit (CPU) platforms.
The good generalization performance of conventional pattern classifiers often relies on the size of training data labeled by costly human labor. These days, publicly available web resources grow explosively, and this allows us to easily obtain abundant and cheap web data. Yet, web data are usually not as cooperative as human labeled data. In this paper, we explore the use of web text data to aid image classification.
Recently, a novel uncoded (pseudoanalog) scheme called SoftCast is proposed for wireless video transmission, which eliminates the cliff effect of the state-of-the-art source-channel coding based schemes and achieves linear quality transition within a wide range of channel signal-to-noise ratio. Therefore, SoftCast-like uncoded and hybrid transmission has become an attractive research issue for natural 2-D video. However, very few studies focus on the SoftCast-based wireless transmission of the 3-D video (3DV) currently.
Are you passionate about solving big scientific problems in education through innovative technology and working in a highly multi-disciplinary collaborative environment? Would you like to know more about how computer vision, affective computing and machine learning are helping create new forms of learning and assessment tools?
The aim of this postdoc project is to develop a novel ultrasound methodology that enables non-invasive read-out of the acoustic properties of radiation-sensitive microbubbles in order to construct a dose map. Hereto, acoustic models of wave propagation through soft tissue will be combined with advanced signal processing techniques. The developed methodology will extensively be validated in experimental setups (both in-vitro and in-vivo).
UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) and their Applications
Department of Computer Science
Faculty of Engineering
University of Sheffield
Fully-funded 4-year PhD studentships for research in Speech and Language Technologies (SLT) and their Applications
** Apply now for September 2020 intake. Up to 13 studentships available **