Erico N de Souza
Erico N de Souza
確認したメール アドレス: dal.ca
タイトル
引用先
引用先
Improving fishing pattern detection from satellite AIS using data mining and machine learning
EN de Souza, K Boerder, S Matwin, B Worm
PloS one 11 (7), e0158248, 2016
1372016
Knowledge-based clustering of ship trajectories using density-based approach
B Liu, EN de Souza, S Matwin, M Sydow
2014 IEEE International Conference on Big Data (Big Data), 603-608, 2014
602014
Trajectorynet: An embedded gps trajectory representation for point-based classification using recurrent neural networks
X Jiang, EN de Souza, A Pesaranghader, B Hu, DL Silver, S Matwin
arXiv preprint arXiv:1705.02636, 2017
352017
Anomaly detection in maritime data based on geometrical analysis of trajectories
BH Soleimani, EN De Souza, C Hilliard, S Matwin
2015 18th International Conference on Information Fusion (Fusion), 1100-1105, 2015
202015
Ship movement anomaly detection using specialized distance measures
B Liu, EN de Souza, C Hilliard, S Matwin
2015 18th International Conference on Information Fusion (Fusion), 1113-1120, 2015
182015
Vessel route anomaly detection with Hadoop MapReduce
X Wang, X Liu, B Liu, EN de Souza, S Matwin
2014 IEEE international conference on big data (big data), 25-30, 2014
182014
Fishing activity detection from ais data using autoencoders
X Jiang, DL Silver, B Hu, EN de Souza, S Matwin
Canadian Conference on Artificial Intelligence, 33-39, 2016
122016
Identifying fishing activities from AIS data with conditional random fields
B Hu, X Jiang, EN de Souza, R Pelot, S Matwin
2016 Federated Conference on Computer Science and Information Systems …, 2016
112016
Extending adaboost to iteratively vary its base classifiers
ÉN de Souza, S Matwin
Canadian Conference on Artificial Intelligence, 384-389, 2011
92011
Network traffic classification using AdaBoost dynamic
EN de Souza, S Matwin, S Fernandes
2013 IEEE International Conference on Communications Workshops (ICC), 1319-1324, 2013
72013
Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification.
X Jiang, EN de Souza, X Liu, BH Soleimani, X Wang, DL Silver, S Matwin
ESANN, 2017
62017
A density-penalized distance measure for clustering
BH Soleimani, S Matwin, EN De Souza
Canadian conference on artificial intelligence, 238-249, 2015
62015
DBMS for web: The future of database management
EN De Souza, E Mota
2006 IEEE International Conference on Information Reuse & Integration, 1-5, 2006
52006
Improvements to adaboost dynamic
EN Souza, S Matwin
Advances in Artificial Intelligence, 2012
42012
Improving point-based AIS trajectory classification with partition-wise gated recurrent units
X Jiang, X Liu, EN de Souza, B Hu, DL Silver, S Matwin
2017 International Joint Conference on Neural Networks (IJCNN), 4044-4051, 2017
32017
Improvements to boosting with data streams
EN de Souza, S Matwin
Canadian Conference on Artificial Intelligence, 248-255, 2013
32013
Improvements to adaboost dynamic
EN de Souza, S Matwin
Canadian Conference on Artificial Intelligence, 293-298, 2012
32012
Automated risk management system
G Henderson, R Sawilla, S Matwin, E Bacic, L Tremblay, ...
Decision making support for continuous improvement of IT mission assurance …, 2012
32012
Traffic classification with on-line ensemble method
EN de Souza, S Matwin, S Fernandes
2014 Global Information Infrastructure and Networking Symposium (GIIS), 1-4, 2014
22014
Extending adaboost: varying the base learners and modifying the weight calculation
E Neves de Souza
Université d'Ottawa/University of Ottawa, 2014
22014
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