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Currently, context has been identified as an important factor in recommender systems. Lots of researches have been done for context-aware collaborative filtering (CF) recommendation, but the contextual parameters in current approaches have same weights for all users. In this paper we propose an approach to learn the weights of contextual parameters for every user based on back-propagation (BP) neural...
Image interpolation is one of the most elementary imaging research topics. A number of image interpolation methods have been developed and tested on uncompressed images in the literature. However, a lot of videos have already been stored or have to be transmitted in compressed format due to the storage limitation or the bandwidth limitation. The existed image interpolation methods may not be efficient...
Context-adaptive binary arithmetic coding (CABAC) is one of the most time-consuming modules in H.264/AVC decoder. A potential way to accelerate CABAC is by parallelization. However, the context modeling process for level information in CABAC is highly serial in nature and can not be parallelized in the coefficient level. In order to improve the throughput of CABAC, in this paper we present a parallel...
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