| Exploiting AIS data for intelligent maritime navigation: A comprehensive survey from data to methodology E Tu, G Zhang, L Rachmawati, E Rajabally, GB Huang IEEE Transactions on Intelligent Transportation Systems, 2017 | 375 | 2017 |
| Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications N Kasabov, NM Scott, E Tu, S Marks, N Sengupta, E Capecci, M Othman, ... Neural Networks 78, 1-14, 2016 | 162 | 2016 |
| Deformed graph Laplacian for semisupervised learning C Gong, T Liu, D Tao, K Fu, E Tu, J Yang IEEE transactions on neural networks and learning systems 26 (10), 2261-2274, 2015 | 136 | 2015 |
| An Automatic Identification System (AIS) Database for Maritime Trajectory Prediction and Data Mining S Mao, E Tu, G Zhang, L Rachmawati, E Rajabally, GB Huang The 7th International Conference on Extreme Learning Machine (ELM2016), 2016 | 131 | 2016 |
| Mapping Temporal Variables Into the NeuCube for Improved Pattern Recognition, Predictive Modeling, and Understanding of Stream Data E Tu, N Kasabov, J Yang IEEE Transactions on Neural Networks and Learning Systems, 2016 | 71 | 2016 |
| A novel graph-based k-means for nonlinear manifold clustering and representative selection E Tu, L Cao, J Yang, N Kasabov Neurocomputing 143, 109-122, 2014 | 64 | 2014 |
| A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification E Tu, Y Zhang, L Zhu, J Yang, N Kasabov Information Sciences 367, 673-688, 2016 | 46 | 2016 |
| NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data E Tu, N Kasabov, M Othman, Y Li, S Worner, J Yang, Z Jia 2014 international joint conference on neural networks (IJCNN), 638-645, 2014 | 42 | 2014 |
| Modeling historical AIS data for vessel path prediction: A comprehensive treatment E Tu, G Zhang, S Mao, L Rachmawati, GB Huang arXiv preprint arXiv:2001.01592, 2020 | 41 | 2020 |
| Design methodology and selected applications of evolving spatio-temporal data machines in the NeuCube neuromorphic framework N Kasabov, N Scott, E Tu, S Marks, N Sengupta, E Capecci, M Othman, ... Neural Networks 78 (2016)), 1-14, 2016 | 33 | 2016 |
| Anomaly3D: Video anomaly detection based on 3D-normality clusters M Asad, J Yang, E Tu, L Chen, X He Journal of Visual Communication and Image Representation 75, 103047, 2021 | 25 | 2021 |
| Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data M Othman, N Kasabov, E Tu, V Feigin, R Krishnamurthi, Z Hou, Y Chen, ... 2014 international joint conference on neural networks (IJCNN), 3197-3204, 2014 | 22 | 2014 |
| Semi-supervised classification with pairwise constraints C Gong, K Fu, Q Wu, E Tu, J Yang Neurocomputing 139, 130-137, 2014 | 21 | 2014 |
| Feasibility of neucube snn architecture for detecting motor execution and motor intention for use in bciapplications D Taylor, N Scott, N Kasabov, E Capecci, E Tu, N Saywell, Y Chen, J Hu, ... 2014 International Joint Conference on Neural Networks (IJCNN), 3221-3225, 2014 | 21 | 2014 |
| Multi-Stream 3D latent feature clustering for abnormality detection in videos M Asad, H Jiang, J Yang, E Tu, AA Malik Applied Intelligence, 1-18, 2022 | 18 | 2022 |
| Infrared super-resolution imaging using multi-scale saliency and deep wavelet residuals G Suryanarayana, E Tu, J Yang Infrared Physics & Technology 97, 177-186, 2019 | 18 | 2019 |
| Remote sensing image automatic registration on multi-scale harris-laplacian W Weixing, C Ting, L Sheng, T Enmei Journal of the Indian Society of Remote Sensing 43, 501-511, 2015 | 18 | 2015 |
| Semi-supervised skin lesion segmentation with learning model confidence Z Xie, E Tu, H Zheng, Y Gu, J Yang ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 17 | 2021 |
| A spatio-temporal fully convolutional network for breast lesion segmentation in DCE-MRI M Chen, H Zheng, C Lu, E Tu, J Yang, N Kasabov Neural Information Processing: 25th International Conference, ICONIP 2018 …, 2018 | 17 | 2018 |
| A review of semi supervised learning theories and recent advances E Tu, J Yang arXiv preprint arXiv:1905.11590, 2019 | 16 | 2019 |
Jie YangShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
