Missing data detection and imputation for urban ANPR system using an iterative tensor decomposition approach

[1]  Jiawei Wang,et al.  Missing traffic data imputation and pattern discovery with a Bayesian augmented tensor factorization model , 2019, Transportation Research Part C: Emerging Technologies.

[2]  Huachun Tan,et al.  A Fused CP Factorization Method for Incomplete Tensors , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[3]  Lijun Sun,et al.  A Bayesian tensor decomposition approach for spatiotemporal traffic data imputation , 2019, Transportation Research Part C: Emerging Technologies.

[4]  Zhiyuan Liu,et al.  A tensor-based Bayesian probabilistic model for citywide personalized travel time estimation , 2018 .

[5]  Xinyu Chen,et al.  Spatial-temporal traffic speed patterns discovery and incomplete data recovery via SVD-combined tensor decomposition , 2018 .

[6]  A. Kibangou,et al.  Traffic data imputation via tensor completion based on soft thresholding of Tucker core , 2017 .

[7]  Kay W. Axhausen,et al.  Understanding urban mobility patterns with a probabilistic tensor factorization framework , 2016 .

[8]  Johan A. K. Suykens,et al.  Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[9]  Bin Ran,et al.  Tensor based missing traffic data completion with spatial–temporal correlation , 2016 .

[10]  Bin Ran,et al.  Short-Term Traffic Prediction Based on Dynamic Tensor Completion , 2016, IEEE Transactions on Intelligent Transportation Systems.

[11]  Andrzej Cichocki,et al.  Smooth PARAFAC Decomposition for Tensor Completion , 2015, IEEE Transactions on Signal Processing.

[12]  Fabien Moutarde,et al.  Analysis of Large-Scale Traffic Dynamics in an Urban Transportation Network Using Non-Negative Tensor Factorization , 2014, International Journal of Intelligent Transportation Systems Research.

[13]  Shuzhong Zhang,et al.  On optimal low rank Tucker approximation for tensors: the case for an adjustable core size , 2015, J. Glob. Optim..

[14]  Jianqiang Wang,et al.  Longitudinal collision mitigation via coordinated braking of multiple vehicles using model predictive control , 2015, Integr. Comput. Aided Eng..

[15]  Liqing Zhang,et al.  Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Bin Ran,et al.  Robust Missing Traffic Flow Imputation Considering Nonnegativity and Road Capacity , 2014 .

[17]  Konstantinos Kalpakis,et al.  Detecting Road Traffic Events by Coupling Multiple Timeseries With a Nonparametric Bayesian Method , 2014, IEEE Transactions on Intelligent Transportation Systems.

[18]  H. Liao,et al.  Simultaneous tensor decomposition and completion using factor priors. , 2014, IEEE transactions on pattern analysis and machine intelligence.

[19]  Huachun Tan,et al.  Low Multilinear Rank Approximation of Tensors and Application in Missing Traffic Data , 2014 .

[20]  Li Li,et al.  Efficient missing data imputing for traffic flow by considering temporal and spatial dependence , 2013 .

[21]  Kamarul Hawari,et al.  Development of automatic vehicle plate detection system , 2013, 2013 IEEE 3rd International Conference on System Engineering and Technology.

[22]  Atul Patel,et al.  Automatic Number Plate Recognition System (ANPR): A Survey , 2013 .

[23]  Guangdong Feng,et al.  A Tensor Based Method for Missing Traffic Data Completion , 2013 .

[24]  Lei Zhang,et al.  An Adaptive Longitudinal Driving Assistance System Based on Driver Characteristics , 2013, IEEE Transactions on Intelligent Transportation Systems.

[25]  Bin Ran,et al.  Perspectives on Future Transportation Research: Impact of Intelligent Transportation System Technologies on Next-Generation Transportation Modeling , 2012, J. Intell. Transp. Syst..

[26]  Yin Wang,et al.  The retrieval of intra-day trend and its influence on traffic prediction , 2012 .

[27]  Fei-Yue Wang,et al.  Data-Driven Intelligent Transportation Systems: A Survey , 2011, IEEE Transactions on Intelligent Transportation Systems.

[28]  Henry Leung,et al.  Data fusion in intelligent transportation systems: Progress and challenges - A survey , 2011, Inf. Fusion.

[29]  Tamara G. Kolda,et al.  Scalable Tensor Factorizations for Incomplete Data , 2010, ArXiv.

[30]  Ioannis Papamichail,et al.  Optimal mainstream traffic flow control of large-scale motorway networks , 2010 .

[31]  Shi Hua-ji,et al.  Short-term traffic flow forecasting model under missing data , 2010 .

[32]  L. Craig Davis,et al.  Introduction to Modern Traffic Flow Theory and Control: The Long Road to Three-Phase Traffic Theory , 2009 .

[33]  Yi Zhang,et al.  PPCA-Based Missing Data Imputation for Traffic Flow Volume: A Systematical Approach , 2009, IEEE Transactions on Intelligent Transportation Systems.

[34]  Tamara G. Kolda,et al.  Tensor Decompositions and Applications , 2009, SIAM Rev..

[35]  Yi Zhang,et al.  A BPCA based missing value imputing method for traffic flow volume data , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[36]  Angshuman Guin,et al.  Multiple Imputation Scheme for Overcoming the Missing Values and Variability Issues in ITS Data , 2005 .

[37]  William T. Scherer,et al.  Exploring Imputation Techniques for Missing Data in Transportation Management Systems , 2003 .

[38]  J. Shao,et al.  Nearest Neighbor Imputation for Survey Data , 2000 .

[39]  Joseph L Schafer,et al.  Analysis of Incomplete Multivariate Data , 1997 .

[40]  J. Chang,et al.  Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .

[41]  L. Tucker,et al.  Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.

[42]  J. Levin.  Three-mode factor analysis. , 1965, Psychological bulletin.

[43]  F. L. Hitchcock.  Multiple Invariants and Generalized Rank of a P‐Way Matrix or Tensor , 1928 .

[44]  F. L. Hitchcock.  The Expression of a Tensor or a Polyadic as a Sum of Products , 1927 .