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The use of cloud storage services has increased rapidly in many organizations. However, the security of data stored in the cloud still remains major concerns. Due to risks of service availability failure and the possibility of malicious insiders in the single cloud, researches about "multi-clouds" have emerged recently. Recent researches that are related to multi-clouds have some limitations...
Recently, dictionary learned by sparse coding has been widely adopted in image classification and has achieved competitive performance. Sparse coding is capable of reducing the reconstruction error in transforming low-level descriptors into compact mid-level features. Nevertheless, dictionary learned by sparse coding does not have the ability to distinguish different classes. That is to say, it is...
A relatively unexplored problem in facial expression analysis is how to select the positive and negative samples with which to train classifiers for expression recognition. Typically, for each action unit (AU) or other expression, the peak frames are selected as positive class and the negative samples are selected from other AUs. This approach suffers from at least two drawbacks. One, because many...
For the reliable video transmission in bandwidth-limited overlay multicast network (OMN), a nonlinear sampling control model is proposed to extract the key frames in video packet sequence of compressed domain according to the characteristics of video packets transmitted in OMN. In the model, weighted membership function and discriminating rules are defined, and key frames are sampled nonlinearly among...
In this paper, we focus on the combined method of SBR and GMM-UBM and its capacity for detection and robustness of speaker recognition. While each method has achieved improvements independent of each other in an orthogonal field, both methods have a similar framework. The proposed Signal Bias Removal based GMM (SBR-GMM) executes the minimization of the environmental variation on mismatched condition...
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