A wide variety of applications in forensic, government, and commercial fields require reliable personal identification. However, the recognition performance is severely affected when encountering non-ideal images caus...
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A wide variety of applications in forensic, government, and commercial fields require reliable personal identification. However, the recognition performance is severely affected when encountering non-ideal images caused by motion blur, poor contrast, various expressions, or illumination artifacts. In this paper, we investigated the use of shape-based eyebrow features under non-ideal imaging conditions for biometric recognition and gender classification. We extracted various shape-based features from the eyebrow images and compared three different classification methods: Minimum Distance Classifier (MD), Linear Discriminant Analysis Classifier (LDA) and Sup- port Vector Machine Classifier (SVM). The methods were tested on images from two publicly available facial im- age databases: The Multiple Biometric Grand Challenge (MBGC) database and the Face Recognition Grand Challenge (FRGC) database. Obtained recognition rates of 90% using the MBGC database and 75% using the FRGC database as well as gender classification recognition rates of 96% and 97% for each database respectively, suggests the shape-based eyebrow features maybe be used for bio- metric recognition and soft biometric classification.
In this paper, impedance control is discussed for multi-point human-robot interaction. The impedance parameters at each interaction point are obtained by taking the environment dynamics into consideration. An optimiza...
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Rough set theory, proposed by Pawlak, has been proved to be a mathematical tool to deal with vagueness and uncertainty in intelligent information processing. In this paper, we propose the concept of knowledge granulat...
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This article is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component individually? We prove that under som...
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Spectral unmixing is a fast growing area in hyperspectral image analysis. Many algorithms have been recently developed to retrieve pure spectral components (endmembers) and determine their abundance fractions in mixed...
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CUDA has become a very popular programming paradigm in parallel computing area. However, very little work has been done for characterizing CUDA kernels. In this work, we measure the thread level performance, collect t...
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CUDA has become a very popular programming paradigm in parallel computing area. However, very little work has been done for characterizing CUDA kernels. In this work, we measure the thread level performance, collect the basic block level characteristics, and glean the instruction level properties for about 35 programs from CUDA SDK, Parboil, and Rodinia benchmark suites. In addition, we define basic block vectors, synchronization vectors and thread similarity matrix to capture the characteristics of CUDA programs efficiently. We find that CUDA programs have some unique characteristics at each level compared to sequential programs.
Offline analysis pipelines have been developed and evaluated for the detection of covert attention from electroen-cephalography recordings, and the detection of overt attention in terms of eye movement based on electr...
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We present a black-box attack that is able to fully recover the secret values shared between entities involved in an authentication protocol. First, we explain how this black-box technique can be successfully applied ...
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As researchers push for Exascale computing, one of the emerging challenges is system resilience. Unlike fault-tolerance which corrects errors, recent reports suggest that resilient systems will need to continue to mak...
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