Variational deep embedding: An unsupervised and generative approach to clustering Z Jiang, Y Zheng, H Tan, B Tang, H Zhou arXiv preprint arXiv:1611.05148, 2016 | 520 | 2016 |

A hybrid deep learning based traffic flow prediction method and its understanding Y Wu, H Tan, L Qin, B Ran, Z Jiang Transportation Research Part C: Emerging Technologies 90, 166-180, 2018 | 505 | 2018 |

A tensor-based method for missing traffic data completion H Tan, G Feng, J Feng, W Wang, YJ Zhang, F Li Transportation Research Part C: Emerging Technologies 28, 15-27, 2013 | 304 | 2013 |

Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework Y Wu, H Tan arXiv preprint arXiv:1612.01022, 2016 | 290 | 2016 |

Short-term traffic prediction based on dynamic tensor completion H Tan, Y Wu, B Shen, PJ Jin, B Ran IEEE Transactions on Intelligent Transportation Systems 17 (8), 2123-2133, 2016 | 175 | 2016 |

Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus Y Wu, H Tan, J Peng, H Zhang, H He Applied energy 247, 454-466, 2019 | 162 | 2019 |

Tensor based missing traffic data completion with spatial–temporal correlation B Ran, H Tan, Y Wu, PJ Jin Physica A: Statistical Mechanics and its Applications 446, 54-63, 2016 | 110 | 2016 |

Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle R Lian, J Peng, Y Wu, H Tan, H Zhang Energy 197, 117297, 2020 | 109 | 2020 |

A novel curve lane detection based on Improved River Flow and RANSA H Tan, Y Zhou, Y Zhu, D Yao, K Li 17th international ieee conference on intelligent transportation systems …, 2014 | 92 | 2014 |

Energy management of hybrid electric bus based on deep reinforcement learning in continuous state and action space H Tan, H Zhang, J Peng, Z Jiang, Y Wu Energy Conversion and Management 195, 548-560, 2019 | 88 | 2019 |

Tensor completion via a multi-linear low-n-rank factorization model H Tan, B Cheng, W Wang, YJ Zhang, B Ran Neurocomputing 133, 161-169, 2014 | 80 | 2014 |

Detecting eye blink states by tracking iris and eyelids H Tan, YJ Zhang Pattern Recognition Letters 27 (6), 667-675, 2006 | 58 | 2006 |

Estimation of missing values in heterogeneous traffic data: application of multimodal deep learning model L Li, B Du, Y Wang, L Qin, H Tan Knowledge-Based Systems 194, 105592, 2020 | 57 | 2020 |

Cross-type transfer for deep reinforcement learning based hybrid electric vehicle energy management R Lian, H Tan, J Peng, Q Li, Y Wu IEEE Transactions on Vehicular Technology 69 (8), 8367-8380, 2020 | 48 | 2020 |

A comparison of traffic flow prediction methods based on DBN H Tan, X Xuan, Y Wu, Z Zhong, B Ran CICTP 2016, 273-283, 2016 | 48 | 2016 |

人脸表情识别研究的新进展 刘晓， 谭春华， 章毓晋 中国图象图形学报 11 (10), 1359r1368, 2006 | 46 | 2006 |

Traffic volume data outlier recovery via tensor model H Tan, J Feng, G Feng, W Wang, YJ Zhang Mathematical Problems in Engineering 2013, 2013 | 44 | 2013 |

Traffic speed data imputation method based on tensor completion B Ran, H Tan, J Feng, Y Liu, W Wang Computational intelligence and neuroscience 2015, 2015 | 43 | 2015 |

A framework for function allocations in intelligent driver interface design for comfort and safety W Wang, F Hou, H Tan, H Bubb International Journal of Computational Intelligence Systems 3 (5), 531-541, 2010 | 41 | 2010 |

Robust missing traffic flow imputation considering nonnegativity and road capacity H Tan, Y Wu, B Cheng, W Wang, B Ran Mathematical Problems in Engineering 2014, 2014 | 39 | 2014 |