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This paper presents a novel automatic nasopharyngeal carcinoma segmentation approach used in magnetic resonance images. Adaptive calculation of the nasopharyngeal region location is first performed. The contour of the tumor is determined through distance regularized level set evolution with the initial contour obtained by the nearest neighbor graph model.(More)
Hysteretic optimization (HO) is a recently proposed optimization method based on the well-known demagnetization process of magnetic materials in physics. In this study, we apply HO to the protein folding problem, an attractive problem in computational biology, by generalizing the external field. The experimental results with benchmark problems show the(More)
This paper proposes a novel compressive sensing based perceptual hashing algorithm for visual tracking. Tracking object is represented by compressive perceptual hashing feature combined with patch-based appearance model. Besides, an updating foreground weight map is assigned for each object representation and the weight map is updated according to the(More)
Recently, with the rapid development of cloud computing, the number of cloud based-applications and cloud server providers have been increasing rapidly, which makes maximizing the efficient use of the cloud server an important research problem. The so-called server consolidation is a technology that uses limited server resources to improve the resource(More)
Much of the previous work in the protein field focused on the 2D protein folding due to its simplicity but ignored the 3D protein folding problem. In this paper, based on the work of 2D protein folding problem by primary extremal optimization (EO) algorithm, we study the more complicated 3D protein folding problem with its variation (τ-EO) for the(More)
Vehicle tracking, significant in the computer vision using machine learning method, allows the vehicle to comprehend its immediate environment and therefore, enhances the intelligence of the vehicles and the safety of vehicle occupants. We propose a novel tracking algorithm that can work robustly under challenging circumstances such as road scene where(More)
Robust online visual tracking is a challenging task of the computer vision due to its violent variation within the video sequences. To approach these issues, deep networks have been applied in order to improve accuracy and correlation filter based trackers perform excellent efficiency and adaptation to scale. In this paper, we present a novel method with(More)
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