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  • Browsing 08 Information and Computing Sciences by Title

Browsing 08 Information and Computing Sciences by Title

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  • Feature Enhancement Using Gradient Salience on Thermal Image 
    Li Zelin; Zhang Jian; Wu Qiang; Geers Glen (IEEE Computer Society, 2010)
    Feature enhancement in an image is to reinforce some exacted features so that it can be used for object classification and detection. As the thermal image is lack of texture and colorful information, the techniques for ...
  • Feature Extraction For FMRI-based Human Brain Activity Recognition 
    Bian Wei; Li Jing; Tao Dacheng (Springer-Verlag Berlin, 2010)
    Mitchell et al. [9] demonstrated that support vector machines (SVM) are effective to classify the cognitive state of a human subject based on fRMI images observed over a single time interval. However, the direct use of ...
  • Feature extraction techniques for abandoned object classification in video surveillance 
    Otoom Ahmed; Piccardi Massimo; Gunes Hatice (IEEE, 2008)
    We address the problem of abandoned object classification in video surveillance. Our aim is to determine (i) which feature extraction technique proves more useful for accurate object classification in a video surveillance ...
  • Feature fusion for 3D hand gesture recognition by learning a shared hidden space 
    Cheng Jun; Xie Can; Bian Wei; Tao Dacheng (Elsevier, 2012)
    Hand gesture recognition has been intensively applied in various human¿computer interaction (HCI) systems. Different hand gesture recognition methods were developed based on particular features, e.g., gesture trajectories ...
  • Feature Level Analysis For 3D Facial Expression Recognition 
    Sha T; Song Mingli; Bu Jj; Chen Chih-Yu; Tao Dacheng (Elsevier Science Bv, 2011)
    3D facial expression recognition has great potential in human computer interaction and intelligent robot systems. In this paper, we propose a two-step approach which combines both the feature selection and the feature ...
  • Feature Selection For Datasets With Imbalanced Class Distributions 
    Kamal Abu; Zhu Xingquan; Pandya Abhijit; Hsu Sam; Narayanan Ramaswamy (World Scientific Publ Co Pte Ltd, 2010)
    Feature selection for supervised learning concerns the problem of selecting a number of important features (w.r.t. the class labels) for the purposes of training accurate prediction models. Traditional feature selection ...
  • Feature Selection of Imbalanced Gene Expression Microarray Data 
    Anaissi Ali Hassan; Kennedy Paul; Goyal Madhu (IEEE Computer Society, 2011)
    Gene expression data is a very complex data set characterised by abundant numbers of features but with a low number of observations. However, only a small number of these features are relevant to an outcome of interest. ...
  • Feature selection using hierarchical feature clustering 
    Liu Huawei; Wu Xindong; Zhang Shichao (ACM, 2011)
    One of the challenges in data mining is the dimensionality of data, which is often very high and prevalent in many domains, such as text categorization and bio-informatics. The high-dimensionality of data may bring many ...
  • Feature Selection with Biased Sample Distributions 
    Kamal Abu; Zhu Xingquan; Pandya Abhijit; Hsu Sam (IEEE Computer Society, 2009)
    Feature selection concerns the problem of selecting a number of important features (w.r.t. the class labels) in order to build accurate prediction models. Traditional feature selection methods, however, fail to take the ...
  • Feature significance for multivariate kernel density estimation 
    Duong Tarn; Cowling Arianna; Koch Inge; Wand Matt (Elsevier, 2008)
    Multivariate kernel density estimation provides information about structure in data. Feature significance is a technique for deciding whether features¿such as local extrema¿are statistically significant. This paper proposes ...
  • Feature Subset Selection Using Differential Evolution 
    Khushaba Rami N; Al-Ani Ahmed; Al-Jumaily Adel (Springer Berlin / Heidelberg, 2009)
    One of the fundamental motivations for feature selection is to overcome the curse of dimensionality. A novel feature selection algorithm is developed in this chapter based on a combination of Differential Evolution (DE) ...
  • The feel dimension of technology interaction:exploring tangibles through movement and touch 
    Robertson Toni; Larssen Astrid Twenebowa; Edwards Jennifer (Association for Computing Machinery, 2007)
    This paper presents concepts to extend our understandings of bodily aspects of technology interactions. The aim of the paper is to offer a way of looking at the role our haptic and kinaesthetic senses play in experiencing ...
  • FIAC: a resource discovery-based two-level admission control for differentiated service networks 
    Li Ming; Hoang Doan (Elsevier, 2007)
  • FICC-DiffServ: A new QoS architecture supporting resources discovery, admission and congestion controls 
    Phan Ha Trung; Hoang Doan (The Institute of Electrical and Electronic Engineers Inc (IEEE), 2005)
    Differentiated Services (DiffServ) QoS architecture is scalable but inadequate to deal with network congestion and unable to provide fairness among its traffic aggregates. Recently, IETF has recommended additional functions ...
  • Field studies of requirements engineering in a multi-site software development organization: research in progress 
    Damian Daniela; Zowghi Didar; Offen Ray (University of New South Wales, 2001)
    In this paper we report on our ongoing research into Requirements Engineering practices in a large multi-site software organization. The findings of a field study conducted at the company's site in Australia are presented ...
  • Filter-based resolution principle for lattice-valued propositional logic LP(X) 
    Ma Jun; Li Wenjiang; Ruan Da; Xu Yang (Elsevier Science, 2002)
  • Filtering Knowledge in Software Design 
    Maung Win (Information Institute, 2003)
    Software design for Human Computer Interaction (HCI) deals with all aspects of the human use of computers, usually in the context of interactive information systems. HCI is concerned with methods, media and mechanisms ...
  • First-class patterns 
    Jay Barry; Kesner D (Cambridge Univ Press, 2009)
    Pure pattern calculus supports pattern-matching functions in which patterns are first-class citizens that can be passed as parameters, evaluated and returned as results. This new expressive power supports two new forms of ...
  • The Fish-Eye Visualization of foreign Currency Exchange Data Streams 
    Lin Li; Cao Longbing; Zhang Chengqi (Australian Computer Society, 2005)
    In a foreign currency exchange market, there are highdensity data streams. The present approaches for visualization of this type of data cannot show us a figure with targeted both local details and global trend information. ...
  • Fitting Multiple Connected Ellipses To An Image Silhouette Hierarchically 
    Xu Yi Da; Kemp Mc (IEEE-Inst Electrical Electronics Engineers Inc, 2010)
    In this paper, we seek to fit a model, specified in terms of connected ellipses, to an image silhouette. Some algorithms that have attempted this problem are sensitive to initial guesses and also may converge to a wrong ...