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    Chapter and Conference Paper

    The Dynamic Process and Sensitivity Analysis for Debris Flow

    The dynamic process and sensitivity in the debris transportation process are important topics in the study of rapid landslides and debris flows. The motion process of debris flow is recognised as a dynamic int...

    Guoqiang Yu, Maosheng Zhang, Hong Chen in Landslide Science for a Safer Geoenvironment (2014)

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    Chapter and Conference Paper

    Combining Iterative Inverse Filter with Shock Filter for Baggage Inspection Image Deblurring

    In this paper, we describe an image deblurring algorithm for images generated by the baggage inspection system. Baggage inspection images have low-extent blurring, large intensity dependent noise and need line...

    Guoqiang Yu, ** Zhang, Li Zhang, Zhiqiang Chen, Yuan**g Li in Computer Vision – ACCV 2006 (2006)

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    Chapter and Conference Paper

    Total Variation Based Iterative Image Reconstruction

    Image reconstruction is an active research field and plays an important role in many applications . In this paper, we propose a new approach. Firstly, we introduce the minimum total variation (TV) criterion in...

    Guoqiang Yu, Liang Li, Jianwei Gu, Li Zhang in Computer Vision for Biomedical Image Appli… (2005)

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    Chapter and Conference Paper

    Short-Term Traffic Flow Forecasting Using Expanded Bayesian Network for Incomplete Data

    In this paper expanded Bayesian network method for short-term traffic flow forecasting in case of incomplete data is proposed. Expanded Bayesian network model is constructed to describe the causal relationship...

    Changshui Zhang, Shiliang Sun, Guoqiang Yu in Advances in Neural Networks - ISNN 2004 (2004)

  5. Chapter and Conference Paper

    Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data

    Traffic flow forecasting is an important issue in the field of Intelligent Transportation Systems. Due to practical limitations, traffic flows recorded can be partially missing or unavailable. In this case few...

    Shiliang Sun, Changshui Zhang, Guoqiang Yu, Naijiang Lu in Machine Learning: ECML 2004 (2004)