Browsing 08 Information and Computing Sciences by Title

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Browsing 08 Information and Computing Sciences by Title

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  • Su, Ya; Gao, Xinbo; Tao, Dacheng; Li, Xuelong (IEEE, 2008)
    Active Appearance Models (AAMs) are generative models which can describe deformable objects. However, the texture in basic AAMs is represented using intensity values. Despite its simplicity, this representation does not ...
  • Gao, Xinbo; Su, Ya; Li, Xuelong; Tao, Dacheng (Elsevier Science Bv, 2009)
    In computer vision applications, Active Appearance Models (AAMs) is usually used to model the shape and the gray-level appearance of an object of interest using statistical methods, such as PCA. However, intensity values ...
  • Li, Xuelong; Maybank, Stephen; Yan, Shuicheng; Tao, Dacheng; Xu, Dong (IEEE-Inst Electrical Electronics Engineers Inc, 2008)
    Human gait is a promising biometrics; resource. In this paper, the information about gait is obtained from the motions of the different parts of the silhouette. The human silhouette is segmented into seven components, ...
  • Kusakunniran, Worapan; Wu, Qiang; Zhang, Jian; Li, Hongdong (IEEE, 2012)
    Gait has been known as an effective biometric feature to identify a person at a distance. However, variation of walking speeds may lead to significant changes to human walking patterns. It causes many difficulties for gait ...
  • Luo, C; Cai, X; Zhang, Jian (IEEE, 2008)
    This paper presents a novel algorithm for robust object tracking based on the particle filtering method employed in recursive Bayesian estimation and image segmentation and optimisation techniques employed in active contour ...
  • Piyathilaka, Jayaweera; Kodagoda, Sarath (IEEE, 2013)
    Ability to recognize human activities will enhance the capabilities of a robot that interacts with humans. However automatic detection of human activities could be challenging due to the individual nature of the activities. ...
  • Jia, Wenjing; Zhang, Huaifeng; Wu, Qiang; He, Sean (IEEE Computer Soc, 2006)
    The conventional histogram intersection (HI) algorithm computes the intersected section of the corresponding color histograms in order to measure the matching rate between two color images. Since this algorithm is strictly ...
  • Zhang, Chengqi; Zhu, Xiaofeng; Zhang, Jilian; Qin, Yongsong; Zhang, Shichao (Springer, 2007)
    Missing data imputation is an actual and challenging issue in machine learning and data mining. This is because missing values in a dataset can generate bias that affects the quality of the learned patterns or the ...
  • Ahadi, Alireza; Lister, Raymond (ACM, 2013)
    ABSTRACT: Computing academics report bimodal grade distributions in their CS1 classes. Some academics believe that such a distribution is due to their being an innate talent for programming, a ?geek gene?, which some ...
  • Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen (IEEE Computer Society, 2007)
    Subspace selection is a powerful tool in data mining. An important subspace method is the Fishera??Rao linear discriminant analysis (LDA), which has been successfully applied in many fields such as biometrics, bioinformatics, ...
  • Brun, Todd; Devetak, Igor; Hsieh, Min-Hsiu (IEEE, 2007)
    Entanglement-assisted quantum error-correcting codes (EAQECCs) make use of pre-existing entanglement between the sender and receiver to boost the rate of transmission. It is possible to construct an EAQECC from any classical ...
  • Smith, David; Abhayapala, Thushara; Aubrey, Timothy (National Committee for Radio Science, 2004)
  • Zhang, Chao; Tao, Dacheng (MIT Press, 2011)
    In this paper, we study the generalization bound for an empirical process of samples independently drawn from an infinitely divisible (ID) distribution, which is termed as the ID empirical process. In particular, based on ...
  • Zhang, Chao; Tao, Dacheng (IEEE-inst Electrical Electronics Engineers Inc, 2012)
    Many existing results on statistical learning theory are based on the assumption that samples are independently and identically distributed (i.i.d.). However, the assumption of i.i.d. samples is not suitable for practical ...
  • Pan, Zb; You, Xg; Chen, H; Tao, Dacheng; Pang, Bc (Elsevier Science Inc, 2013)
    Semi-supervised ranking is a relatively new and important learning problem inspired by many applications. We propose a novel graph-based regularized algorithm which learns the ranking function in the semi-supervised learning ...
  • Li, Tianrui; Yang, Ning; Ma, Jun (Southwest Jiaotong University, 2004)
    To solve the problem that the existing algorithms of mining association rules result in a number of rules, upper closed set of an item set and generalized association rule base were defined. And some important propositions ...
  • Zhao, Yanchang; Zhang, Shichao (IEEE Computer Soc, 2006)
    Recent-biased approximations have received increased attention recently as a mechanism for learning trend patterns from time series or data streams. They have shown promise for clustering time series and incrementally ...
  • Wu, Qiang; Yang, Jie; He, Sean; Wang, William (IEEE, 2013)
    Local Binary Pattern (LBP) has been well recognised and widely used in various texture analysis applications of computer vision and image processing. It integrates properties of texture structural and statistical texture ...
  • Li, Sanjiang; Luo, Maokang (Elsevier Science Bv, 2003)
    According to their value ranges, L-topological spaces form different categories. Clearly, the investigation on their relationships is certainly important and necessary. Lowen was one of the first authors who had studied ...
  • Shannon, Anthony; Atanassov, Krassimir; Riecan, Beloslav; Krawczak, Maciej; Orozova, Daniela; Melo-Pinto, Pedro; Sotirova, Evdokia; Parvathi, Rangasamy; Kim, Taekyun (IEEE, 2012)
    A generalized net model of the process of selection and usage of an intelligent e-learning system is constructed. An evaluation of the results of the learning is done. This work is a follow up of previous authors' research ...