Discovering Human Places of Interest from Multimodal Mobile Phone Data
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Dynamic contrast-enhanced (albumin-Gd-DTPA) magnetic resonance imaging, performed during 2 weeks of daily administration of an inhibitor of tyrosine kinase receptors (SU6668) in an HT-29 colon carcinoma model, revealed the onset of a hyper-enhancing rim, n ...
One of the shortcomings of the existing clustering methods is their problems dealing with different shape and size clusters. On the other hand, most of these methods are designed for especial cluster types or have good performance dealing with particular s ...
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We introduce a fast approach to classification and clustering applicable to high-dimensional continuous data, based on Bayesian mixture models for which explicit computations are available. This permits us to treat classification and clustering in a single ...
This paper aims at investigating the use of sequential clustering for speaker diarization. Conventional diarization systems are based on parametric models and agglomerative clustering. In our previous work we proposed a non-parametric method based on the a ...
Data alone are worth almost nothing. While data collection is increasing exponentially worldwide, a clear distinction between retrieving data and obtaining knowledge has to be made. Data are retrieved while measuring phenomena or gathering facts. Knowledge ...
Structural Health Monitoring (SMH) has the potential to provide reliable, quantitative data on the real condition of structures. Early detection of damage or deterioration can enable preventive repair and reduce maintenance costs. Although obtaining data f ...
The automatic analysis of real-life, long-term behavior and dynamics of individuals and groups from mobile sensor data constitutes an emerging and challenging domain. We present a framework to classify people's daily routines (defined by day type, and by g ...
The automatic analysis of real-life, long-term behavior and dynamics of individuals and groups from mobile sensor data constitutes an emerging and challenging domain. We present a framework to classify people's daily routines (defined by day type, and by g ...
Co-clustering has not been much exploited in biomedical in- formatics, despite its success in other domains. Most of the previous applications were limited to analyzing gene expression data. We performed co-clustering analysis on other types of data and ob ...
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