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Our measurements on production data center traffic together with recently reported results suggest that data center networks suffer from long-lived congestion caused by core network over subscription and unbalanced workload placement. In contrast to traditional traffic engineering approaches that optimize flow routing, in this paper, we explore the opportunity to address the continuous congestion...
Accurate brain tissue segmentation from magnetic resonance (MR) images is an essential step in quantitative brain image analysis. However, due to the existence of noise and intensity inhomogeneity in brain MR images, many segmentation algorithms suffer from limited accuracy. In this paper, we assume that the local image data within each voxel's neighborhood satisfy the Gaussian mixture model (GMM),...
Content-based document image retrieval is a new and promising research area. Without OCR, document indexing directly based on image content is more general and convenient. However content-based Chinese document retrieval is difficult for the complexity of Chinese character structure and large class numbers. Few papers cover this issue, and this paper will focus on it. This paper presents a novel algorithm...
This paper proposed a general image segmentation model, namely the energy-minimization based image segmentation (EMBIS) model. This model converts image segmentation into a controlled optimization process minimizing the weighted sum of the feature energy and spatial energy, which interpret the homogeneity restriction and spatial constraints, respectively. The EMBIS model provides a unified understanding...
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