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Noise robustness has long garnered much interest from researchers and practitioners of the automatic speech recognition (ASR) community due to its paramount importance to the success of ASR systems. This paper presents a novel approach to improving the noise robustness of speech features, building on top of the dictionary learning paradigm. To this end, we employ the K-SVD method and its variants...
For sparse code multiple access (SCMA) with traditional codebooks, the initial information of message passing algorithm (MPA) receiver is easily susceptible to noise and multipath fading, and the convergence reliability of the first detected user in each decision process is unsatisfactory. Driven by these problems, an optimized codebook design for SCMA is presented in this paper. In the proposed SCMA...
Object proposal is a new paradigm for improving efficiency for object detection. We propose an efficient method for object proposals by saliency seeds and contour segments. A simple saliency method is used to get several salient seeds in the image to target all the probable objects appeared in image, roughly leaving background regions out of consideration. Then we further score each of the salient...
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