Enmei Tu
Cited by
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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
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
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
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
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
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
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
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
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
Semi-supervised classification with pairwise constraints
C Gong, K Fu, Q Wu, E Tu, J Yang
Neurocomputing 139, 130-137, 2014
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
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 (3), 501-511, 2015
Posterior distribution learning (pdl): A novel supervised learning framework using unlabeled samples to improve classification performance
E Tu, J Yang, N Kasabov, Y Zhang
Neurocomputing 157, 173-186, 2015
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
A Review of Semi Supervised Learning Theories and Recent Advances
E Tu, J Yang
arXiv preprint arXiv:1905.11590, 2019
An experimental comparison of semi-supervised learning algorithms for multispectral image classification
E Tu, J Yang, J Fang, Z Jia, N Kasabov
Photogrammetric Engineering & Remote Sensing 79 (4), 347-357, 2013
Efficient multiresolution level set image segmentation with multiple regions
J Fang, J Yang, E Tu, Z Jia, NK Kasabov
Optical Engineering 50 (6), 067005, 2011
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
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
International Conference on Neural Information Processing, 358-368, 2018
Statistical approaches to automatic level set image segmentation with multiple regions
J Fang, J Yang, E Tu, Z Jia, NK Kasabov, C Liu
Optical Engineering 50 (10), 107001, 2011
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