The problem of efficiently finding top-k frequent items has attracted much attention in recent years. Storage constraints in the processing node and intrinsic evolving feature of the data streams are two main challeng...
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ISBN:
(纸本)9781479967162
The problem of efficiently finding top-k frequent items has attracted much attention in recent years. Storage constraints in the processing node and intrinsic evolving feature of the data streams are two main challenges. In this paper, we propose a method to tackle these two challenges based on space-saving and gossip-based algorithms respectively. Our method is implemented on SAMOA, a scalab.e advanced massive online analysis machine learning framework. The experimental results show its effectiveness and scalab.lity.
The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social f...
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A novel and efficient speckle noise reduction algorithm based on wavelet transform by cycle spinning for removing speckle of unknown variance and minimizing the effect of pseudo-Gibbs phenomena from Synthetic Aperture...
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Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper...
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This paper proposes an unobtrusive way to detect fatigue for drivers through grip forces on steering wheel. Simulated driving experiments are conducted in a refitted passenger car, during which grip forces of both han...
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In this paper, we propose a novel compact representation called weighted bipartite hypergraph to exploit the fertility model, which plays a critical role in word alignment. However, estimating the probabilities of rul...
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Independent Component Analysis(ICA)and Common Spatial Patterns(CSP)are commonly used to find spatial filters for classification of electroencephalogram(EEG)signals in motor *** ICA needs physiological knowledge about ...
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Independent Component Analysis(ICA)and Common Spatial Patterns(CSP)are commonly used to find spatial filters for classification of electroencephalogram(EEG)signals in motor *** ICA needs physiological knowledge about the potential changes of task-related EEG signals to select filters manually,this paper proposes to acquire filter information from the spatial filters constructed by CSP,then the improved ICA is compared with CSP from several aspects on BCI competition III dataset IVa as well as dataset of left and right hand motor imagery from our independent *** results suggest the proposed ICA has good classification performance and is better on robustness and flexibility,while CSP is simpler and more suitable for multi-channel EEG.
In this demo, we present ObjectSense, a scalab.e object recognition system that recognizes multiple objects present in a static image or in the camera frames. Instead of applying learning based recognition framework, ...
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