BACKGROUND Functional brain imaging studies have indicated that distinct anatomical brain regions can show coherent spontaneous neuronal activity during rest. Regions that show such correlated behavior are said to form resting-state networks (RSNs). RSNs have been investigated using seed-dependent functional connectivity maps and by using a number of model-free methods. However, examining RSNs ...

and Normalized Cut Clustering Jui-Chen Wu, Jun-Wei Hsieh * , Yung-Sheng Chen, and Cheng-Min Tu Department of Electrical Engineering Yuan Ze University, Taiwan *[email protected] Abstract This paper proposes a novel approach for vehicle orientation detection using “vehicle color” and edge information based on clustering framework. To extract the “vehicle color”, this paper proposes a novel...

Recent advances in the speed and programmability of graphics hardware permit the GPU to grow as a powerful vector coprocessor to the CPU. In this work, the emphasis will be to implement fast Matrix-Vector operations to improve techniques for eigenvalue decomposition. We introduce a framework for the implementation of this mathematical operation, thus providing the building blocks for the design...

The graph cuts in image segmentation have been widely used in recent years because it regards the problem of image partitioning as a graph partitioning issue, a well-known problem in graph theory. The normalized cut approach uses spectral graph properties of the image representative graph to bipartite it into two or more balanced subgraphs, achieving in some cases good results when applying thi...

In this paper, we explore the use of a graph algorithm called the normalized cut in order to organize prominent components of the auditory scene. We focus specifically on defining a time-constrained similarity metric. We show that such a metric can be successfully expressed in terms of the time and frequency masking phenomena and can be used to solve common problems in auditory scene analysis.

We propose using the Normalized Cut method for motion tracking (J. Shi and J. Malik . “Motion Segmentation and Tracking Using Normalized Cuts”. In IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), pages 888 905, 2000) on regions in frames that were identified by a Minimum Spanning Tree (MST) method in a pre-proccessing step. The purpose of the pre-proccessing step is to red...

In imaging data based brain network analysis, a necessary precursor for constructing meaningful brain networks is to identify functionally homogeneous regions of interest (ROIs) for defining network nodes. For parcellating the brain based on resting state fMRI data, normalized cut is one widely used clustering algorithm which groups voxels according to the similarity of functional signals. Due ...

Normalized graph cut (NGC) has become a popular research topic due to its wide applications in a large variety of areas like machine learning and very large scale integration (VLSI) circuit design. Most of traditional NGC methods are based on pairwise relationships (similarities). However, in real-world applications relationships among the vertices (objects) may be more complex than pairwise, w...