Significant research has been devoted to object tracking. Most existing algorithms can track the object well in the controlled environment. However, they may fail in the presence of drastic appearance changes or compl...
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With the rapid development of semiconductor technology, hundreds of processor cores can be integrated into a single chip, known as "many-core system-on-chip". For the problem that performance and power consu...
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Due to the disadvantage of large amounts of data computation and image quality degradation of classical reconstruction algorithm, a novel adaptive method of image reconstruction denoising based on compressive sensing ...
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Due to the disadvantage of large amounts of data computation and image quality degradation of classical reconstruction algorithm, a novel adaptive method of image reconstruction denoising based on compressive sensing is proposed. Firstly, the wavelet approximate coefficients and detail coefficients from the image noise are Gaussian distribution, and have different variances in different levels. Secondly, the noise image is divided into image blocks of a certain size, a new compression sensing block reconstruction method has been used to recover small block coefficients. Finally, the reconstructed denoising images are obtained based on recovered detail coefficients and approximate coefficients by the separation of small block wavelet inversed transform. Experimental results show that this method is feasible and available, compared with pure wavelet denoising and block image, signal-to-noise ratio has been improved highly, the image noise has been removed effectively and the reconstructed image quality has been improved highly.
Cloud computing can dynamically provide service based on service level agreements that between cloud services and consumers. Establish a viable and efficient dynamic negotiation strategy is one of hot research in clou...
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Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The resu...
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Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.
With the rapid development of computer technology, distributed computing and parallel computing have made great progress. Distributed parallel computing system is a combination of distributed computing and parallel co...
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In modern embedded platforms, safety-critical functionalities that must be certified correctly to high level of assurance co-exist with less critical software that are not subjected to certification requirements. Thes...
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Nowadays cloud computing has become a popular platform for scientific applications. Cloud computing intends to share a large scale resources and equipments of computation, storage, information and knowledge for scient...
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The multiframe task has been considered in dynamic real-time scheduling, its different execution mode optional feature can handle the resource waste caused by pessimistic estimation of the execution requirement. But i...
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For the redundant codes caused by software reuse and rapid development in object-oriented program, the paper proposes a cutting model and designs a cutting scheme based on this model. Firstly, a cutting model is estab...
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