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  • Browsing 08 Information and Computing Sciences by Title

Browsing 08 Information and Computing Sciences by Title

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  • A fast data processing procedure for support vector regression 
    Lu Jie; Zhang Guangquan; Hao Zhifeng; Wen W; Yang Xiao (Springer-Verlag, 2006)
    A fast data preprocessing procedure (FDPP) for support vector regression (SYR) is proposed in this paper. In the presented method, the dataset is firstly divided into several subsets and then K-means clustering is implemented ...
  • A Fast Focus + Context Viewing Technique for Web Navigation 
    Nguyen Quang Vinh; Huang Mao (CSREA Press, 2003)
    Most web browsers do not give users a proper visual aid to guide their webjourney. One of the approaches to overcome this problem is to use graphs and trees visualiuztion. This paper presents a simple and fast ...
  • Fast Haar Transform Based Feature Extraction for Face Representation and Recognition 
    Pang Yanwei; Li Xuelong; Yuan Yuan; Tao Dacheng; Pan Jing (IEEE-Inst Electrical Electronics Engineers Inc, 2009)
    Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications ...
  • Fast Indoor Scene Classification Using 3D Point Clouds 
    Shi Lei; Kodagoda Sarath; Ranasinghe Ravindra (The ACRA 2011 Organising Committee, 2011)
    A representation of space that includes both geometric and semantic information enables a robot to perform high-level tasks in complex environments. Identifying and categorizing environments based on onboard sensors are ...
  • Fast simulation of animal locomotion: lamprey swimming 
    Beauregard M; Kennedy Paul; Debenham John (Springer-Verlag, 2006)
    Biologically realistic computer simulation of vertebrate locomotion is an interesting and challenging problem with applications in computer graphics and robotics. One current approach simulates a relatively simple ...
  • Fault Diagnosis of Transformer using Association Rule Mining and Knowledge Base 
    Zhang Tiefeng; Zhang Guangquan; Lu Jie; Ding Qian (IEEE, 2010)
    Association rule mining makes interesting associations and/or correlations among large sets of data. Those associations can be refined as decision rules to be used and stored in a knowledge base system. In this paper, an ...
  • Fault modeling for non-linear systems using ANFIS 
    Khosravi Anas; Lu Jie (Prokom Softwares, 2006)
    In this paper we develop a new method to model occurred faults in different parts of nonlinear systems. Using an Adaptive Neuro-Fuzzy Inference System (ANFIS) we build a model for faultless plant which is used in the ...
  • Fault Tolerance of Embryonic Algorithms in Mobile Networks 
    Lowe David; Mujkanovic Amir; Miorandi Daniel; Yamamoto Lidia (Springer-Verlag Berlin Heidelberg, 2010)
    In previous work the authors have described an approach for building distributed selfâ¿¿healing systems â¿¿ referred to as EmbryoWare â¿¿ that, in analogy to Embryonics in hardware, is inspired by cellular development and ...
  • Feasibility Trial of a Novel Mobile Cardiac Rehabilitation Application 
    Gay Valerie; Leijdekkers Peter; Barin Edwards (IEEE Communications Society, 2010)
    A trial with a cardiac rehabilitation centre is in progress where we test a novel cardiac rehab application using a standard mobile phone and wireless sensors. The goal is to obtain insight how remote monitoring compares ...
  • A Feature Analysis Framework for Evaluating Multi-Agent System Development Methodologies 
    Tran Quynh-Nhu Numi; Low Graham; Williams Mary-Anne (Springer-Verlag, 2003)
    This paper proposes a comprehensive and multi-dimensional feature analysis framework for evaluating and comparing methodologies for developing multi-agent systems (MAS). Developed from a synthesis of various existing evaluation ...
  • 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 ...