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In domain adaptation, maximum mean discrepancy (MMD) has been widely adopted as a discrepancy metric between the distributions of source and target domains. However, existing MMD-based domain adaptation methods generally ignore the changes of class prior distributions, i.e., class weight bias across domains. This remains an open problem but ubiquitous for domain adaptation, which can be caused by...
Variations in trabecular bone texture are known to be correlated with bone diseases, such as osteoporosis. In this paper we propose a multi-feature multi-ROI (MFMR) approach for analyzing trabecular patterns inside the oral cavity using cone beam computed tomography (CBCT) volumes. For each dental CBCT volume, a set of features including fractal dimension, multi-fractal spectrum and gradient based...
As a third-generation universal I/O interconnect technology succeeding ISA and PCI bus, PCI Express has characteristics of lower pin count, higher reliability and faster transfer rate, which makes it a promising prospect. This paper studies PCI Express interface technology of DSP based on KeyStone architecture, and proposes a driver design method aimed at PCI Express interconnection between DSP and...
In this paper, we extend the idea of sparse representation into the high dimensional feature space induced by the kernel function, and propose a kernel based test sample sparse representation and classification algorithm (KTSRC) for the first time. The KTSRC is based on the assumption that the test sample can be linearly represented by a part of the training samples in the high dimensional feature...
A large number of training samples is requiredin developing visual object recognition systems. However, the size of samples is limited sometimes. This paper investigates bagging of one class support vector machines (OCSVM), which just use one class of objects for training. Experiments are performed on Caltech101 database. Our findings show that the performance with bagging method is better than single...
In this paper, we derive an efficient nonlinear feature extraction method from naive Kernel Minimum Squared Error (KMSE) method. The most contribution of the derived method is its feature extraction procedure that is much more computationally efficient than naive KMSE. Differing from naive KMSE that exploits some linear combination of the total training patterns to express the discriminant vector...
In this study, we measure, model and analyze characteristics of traffic flows of P2P application Maze by capturing real traffic from an operational network. Maze is a P2P file-sharing system with a centralized, cluster-based search engine and a social network among peers. We report the models for flow arrival interval, flow size, flow duration and flow rate of Maze traffic flows. With the growing...
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