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With the growing number of audio excerpts through various media and distribution channels, advanced audio analysis approaches have received significant interest in the multimedia field. However, current audio analysis approaches are still far from satisfactory due to the semantic gaps between the low-level acoustic features and high-level semantics perceived by human brain. In order to alleviate the...
Nowadays, there are many movie trailers publicly available on social media website such as YouTube, and many thousands of users have independently indicated whether they like or dislike those trailers. Although it is understandable that there are multiple factors that could influence viewers’ like or dislike of the trailer, we aim to address a preference question in this work: Can subjective multimedia...
Recently, it has been shown that structural connectivity patterns derived from diffusion MRI (dMRI) can be used for cortical parcellation and segmentation. However, most previous methods were based on diffusion tractography, which is limited in depicting local profiles, e.g., in regions beneath the cortical sulcal fundi. Instead, in this paper, we propose to derive effective features directly from...
Localization of functional cortical ROIs (regions of interests) in structural data such as DTI and T1-weighted MRI has significant importance in basic and clinical neuroscience. However, this problem is challenging due to the lack of quantitative mapping between brain structure and function, which relies on both the availability of benchmark training data such as task-based fMRI and effective machine...
Quantitative descriptions of white matter (WM) fiber shape and cortical folding patterns are important for neuroscience research. This paper presents a novel computational method for WM fiber shape pattern analysis, that is, WM fibers are clustered into five primitive shape patterns: closed `U', `M', curved line, open `U' and straight line, based on the automatic clustering of their shape features...
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