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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School of thought analysis is an important yet not-well-elab.rated scientific knowledge discovery task. This paper makes the first attempt at this problem. We focus on one aspect of the problem: do characteristic scho...
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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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Beijing has experienced a rapid urban sprawl over the past three decades, along with accelerated socio-economic development. This study investigated the change patterns and figured out the driving forces of urban expa...
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ISBN:
(纸本)9783037857427
Beijing has experienced a rapid urban sprawl over the past three decades, along with accelerated socio-economic development. This study investigated the change patterns and figured out the driving forces of urban expansion in the study area. To obtain urban class, decision tree classification techniques were used to identify the land cover types using four scenes of Landsat images from four periods of 1978-era, 1992-era, 2000-era and 2010-era. Then, the urban areas were identified by excluding water, agriculture, forest, grassland and bare land. The analysis results showed that: 1) urban construction land had been expanded very quickly and the urban area is mainly in the south-central part of the municipality;2) the urban area increased by 96284.97 ha and the ratio was 5.88%;and 3) population growth, economic development, urban construction and industrial structure adjustment could explain the expansion. These analysis results can provide significant information on the monitoring and management of sustainable urban development.
Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as t...
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Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as the structure of P systems, the way of communication between cells, etc. Membrane algorithms are a kind of parallel methods, where many operations can be performed in parallel. Although the importance of the parallelism of such algorithms is recognized, membrane algorithms were often implemented on the serial computing device Central processing Unit (CPU), which makes the algorithms cannot work in a more efficient way. In this work, we consider the implementation of membrane algorithms on the parallel computing device Graphics processing Unit (GPU). Under such implementation, all cells of membrane algorithms can work simultaneously. Experiment results on two classical intractable problems, point set matching problem and TSP, show that GPU implementation of membrane algorithms is much more efficient than CPU implementation in terms of runtime, especially for solving the problems with a high complexity.
Recent years have witnessed the growing popularity of hashing for efficient large-scale similarity search. It has been shown that the hashing quality could be boosted by hash function learning (HFL). In this paper, we...
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ISBN:
(纸本)9781577356332
Recent years have witnessed the growing popularity of hashing for efficient large-scale similarity search. It has been shown that the hashing quality could be boosted by hash function learning (HFL). In this paper, we study HFL in the context of multimodal data for cross-view similarity search. We present a novel multimodal HFL method, called Parametric Local Multimodal Hashing (PLMH), which learns a set of hash functions to locally adapt to the data structure of each modality. To balance locality and computational efficiency, the hashing projection matrix of each instance is parameterized, with guaranteed approximation error bound, as a linear combination of basis hashing projections of a small set of anchor points. A local optimal conjugate gradient algorithm is designed to learn the hash functions for each bit, and the overall hash codes are learned in a sequential manner to progressively minimize the bias. Experimental evaluations on cross-media retrieval tasks demonstrate that PLMH performs competitively against the state-of-the-art methods.
This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-tra...
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This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-transform-based finite-difference time-domain (ZTFDTD) method was presented for simulating the interaction of electromagnetic wave with unmagnetized *** using the newly introduced Compute Unified Device Architecture (CUDA) technology, we illustrate the efficacy of GPU in accelerating the FDTD computations by achieving significant speedups with great ease and at no extra hardware *** effect of the GPU-CPU memory transfers on the speedup will be also studied.
In this demo paper we present a multiscale browsing interface for handheld devices, in which the user can interactively change the scale of the storyboard to easily adjust the amount of information desired. Convention...
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Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a uni...
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