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Methods of critical value reduction for type-2 fuzzy variables and their applications
A type-2 fuzzy variable is a map from a fuzzy possibility space to the real number space; it is an appropriate tool for describing type-2 fuzziness. This paper first presents three kinds of criticalExpand
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Type-2 fuzzy variables and their arithmetic
This paper proposes an axiomatic framework from which we develop the theory of type-2 (T2) fuzziness, called fuzzy possibility theory. First, we introduce the concept of a fuzzy possibility measureExpand
  • 71
  • 14
Self-splitting competitive learning: a new on-line clustering paradigm
  • Y. Zhang, Z. Liu
  • Computer Science, Medicine
  • IEEE Trans. Neural Networks
  • 1 March 2002
Clustering in the neural-network literature is generally based on the competitive learning paradigm. The paper addresses two major issues associated with conventional competitive learning, namely,Expand
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  • 10
  • Open Access
A robust, real-time ellipse detector
  • S. Zhang, Z. Liu
  • Mathematics, Computer Science
  • Pattern Recognit.
  • 1 February 2005
Abstract In this paper, we present an improved ellipse detector that may be used in real-time face detection. In this algorithm we first extract edges from the image using a robust edge detector,Expand
  • 135
  • 9
A coupled HMM approach to video-realistic speech animation
  • L. Xie, Z. Liu
  • Computer Science
  • Pattern Recognit.
  • 1 August 2007
We propose a coupled hidden Markov model (CHMM) approach to video-realistic speech animation, which realizes realistic facial animations driven by speaker independent continuous speech. DifferentExpand
  • 61
  • 8
  • Open Access
Word recognition using fuzzy logic
This paper presents an offline word-recognition system based on structural information in the unconstrained written word. Oriented features in the word are extracted with the Gabor filters. WeExpand
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  • Open Access
Dynamical cognitive network - an extension of fuzzy cognitive map
We present the dynamic cognitive network (DCN) which is an extension of the fuzzy cognitive map (FCM). Each concept in the DCNs can have its own value set, depending on how precisely it needs to beExpand
  • 146
  • 5
Contextual fuzzy cognitive map for decision support in geographic information systems
Fuzzy cognitive maps or FCMs have been shown to be useful when representing qualitative data. We have shown that these FCM structures can be used to represent quantitative and qualitative data. WeExpand
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  • 5
Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network
We propose a heterogeneous multi-task learning framework for human pose estimation from monocular images using a deep convolutional neural network. In particular, we simultaneously learn a human poseExpand
  • 135
  • 5
  • Open Access
Handwriting Recognition - Soft Computing and Probabilistic Approaches
  • Z. Liu, J. Cai, R. Buse
  • Computer Science
  • Studies in Fuzziness and Soft Computing
  • 10 September 2003
In this book, we introduce several methods for recognising unconstrained handwritten words and digits using hidden Markov models (HMMs) and Markov random field (MRF) models. Since the hidden MarkovExpand
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  • 5
  • Open Access