Recent years have seen an increasing interest in clustering data comprising multiple domains or modalities, such as categorical, numerical and transactional, etc. This kind of data is sometimes found within the contex...
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The personal photo retrieval task at ImageCLEF 2012 is a pilot task for testing QBE-based retrieval scenarios in the scope of personal information retrieval. This pilot task is organized as two subtasks: the visual co...
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The personal photo retrieval task at ImageCLEF 2012 is a pilot task for testing QBE-based retrieval scenarios in the scope of personal information retrieval. This pilot task is organized as two subtasks: the visual concepts retrieval and the events retrieval. In this paper, we develop a framework of combining different visual features, EXIF data and similarity measures based on two clustering methods to retrieve the relevant images having similar visual concepts. We first analyze and select the effective visual features including color, shape, texture, and descriptor to be the basic elements of recognition. A flexible similarity measure is then given to achieve high precise image retrieval automatically. The experimental results show that the proposed framework can provide good effectiveness in distinct measures of evaluation.
The task of visual concept detection, annotation, and retrieval using Flickr photos at ImageCLEF 2012 was organized as two subtasks: concept annotation and concept retrieval. In this paper, we present the effort of KI...
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The task of visual concept detection, annotation, and retrieval using Flickr photos at ImageCLEF 2012 was organized as two subtasks: concept annotation and concept retrieval. In this paper, we present the effort of KIDS lab for the two subtasks. The proposed approaches combine various visual and textual features, dimension reduction methods, the random forest classification models, and the semi-supervised learning strategy. For the concept annotation subtask, the annotation results show that combination of tags and visual features outperforms visual-only features while using the same classification model. The results also show that semi-supervised learning is not superior to supervised learning in this subtask. Further, it does not seem able to gain more advantage on F-measure when more different visual features were used. For the concept retrieval task, the results illustrate that the textual features contain much richer informatics than visual features in general retrieved concepts.
Measuring semantic relatedness plays an important role in information retrieval and Natural Language Processing. However, little attention has been paid to measuring semantic relatedness between named entities, which ...
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Using web standards, such as uniform resource identifiers (URIs), XML and HTTP, for naming and describing resources which are not information objects is the key difference between the Web as we know it today and the S...
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This poster presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.
ISBN:
(纸本)9781450316507
This poster presents a preliminary study on the PerturBoost approach that aims to provide efficient and secure classifier learning in the cloud with both data and model privacy preserved.
The Linking Open Data (LOD) project is an ongoing effort to construct a global data space, i.e. the Web of Data. One important part of this project is to establish owl:sameAs links among structured data sources. Such ...
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Heart rate variability (HRV) power spectrum analysis is a well-known technique used to study the activity of the autonomic nervous system. It is performed by calculating the spectral power of certain bands of the RR t...
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ISBN:
(纸本)9789898425898
Heart rate variability (HRV) power spectrum analysis is a well-known technique used to study the activity of the autonomic nervous system. It is performed by calculating the spectral power of certain bands of the RR time series. There are several tools that perform this type of analysis: Kubios HRV, PhysioNet's HRV toolkit for MatLab and aHRV, among others. All these tools use the Short Fourier Transform to estimate spectral power. However, the RR time series is a non-stationary signal. The Wavelet transform is often a more suitable tool for analyzing non-stationary signals than the Short Time Fourier Transform. Its usefulness in HRV analysis has already been proven in the literature. However, the lack of HRV analysis tools that support it has made this technique underutilized in HRV studies. In this paper we present an extension to the RHRV opensource package that enables Wavelet-based HRV spectral analysis. Until now this package only supported HRV spectral analysis based on the Fourier transform.
In a previous work [12, 11], the authors proposed SPAN: a learning algorithm based on temporal coding for Spiking Neural Network (SNN). The algorithm trains a neuron to associate target spike patterns to input spatio-...
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