A simple method is proposed to estimate the DOA using acoustic vector sensor in the presence of nonuniform noise. Algorithms mentioned in earlier works are shown to be susceptible to choice of weighted parameter. The ...
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This paper is a continuation of previous published work by the same authors on Personalized Modelling and Evolving Spiking Neural Network Reservoir architecture (PMeSNNr). The focus is on improvement of predictive mod...
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ISBN:
(纸本)9781479914821
This paper is a continuation of previous published work by the same authors on Personalized Modelling and Evolving Spiking Neural Network Reservoir architecture (PMeSNNr). The focus is on improvement of predictive modeling methods for the stroke occurrences case study utilizing an enhanced NeuCube architecture. The adaptability of the new architecture leads towards understanding feature correlations that affect the outcome of the study and extracts new knowledge from hidden patterns that reside within the associations. Through this new method, estimation of the earliest time point for stroke prediction is possible. This study also highlighted the improvement from designing a new experimental dataset compared to previous experiments. Comparative experiments were also carried out using conventional machine learning algorithms such as kNN, wkNN, SVM and MLP to prove that our approach can result in much better accuracy level.
We present a non-rigid object matching algorithm based on hyper graph method. Previous work has achieved good performance for rigid object matching. However, because of deformation and wrinkle, existing algorithms can...
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Aiming at the adverse influence of correlation between measurement noise and process noise for filtering precision in nonlinear system estimation, Firstly, Rao-Blackwellised modeling technique is introduced to disasse...
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Hyper-graph matching algorithm describes the whole structure of object by high-order topology. Previous work has presented many methods to build and solve the problem model. This paper mainly focuses on feature descri...
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As one of the most traditional tracking methods, particle filter has been improved in many previous tracking methods due to its non-Gaussian and non-linear distribution. Meanwhile, pure tracking methods cannot achieve...
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Parallel coordinate descent algorithms emerge with the growing demand of large-scale optimization. In general, previous algorithms are usually limited by their divergence under high degree of parallelism (DOP), or nee...
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This paper proposes an automatic salient object extraction framework. Firstly, the saliency model are developed by applying the low level color features and the boundary prior. The initial salient regions are extracte...
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We propose a novel framework for automatic image segmentation. In this approach, a mixture of several over-segmentation methods are used to produce superpixels and then aggregation is achieved using a cluster ensemble...
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In this paper, we take the advantages of color contrast and color distribution to get high quality saliency maps. The overall procedure flow of our unified framework contains superpixel pre-segmentation, color contras...
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