Self-learning adaptive algorithm for maritime traffic abnormal movement detection based on virtual pheromone method. - Julius Venskus; Mindaugas Kurmis; Arunas Andziulis; Zydrunas Lukosius; Miroslav Voznák; Denisas Bykovas (SPECTS@SummerSim, 2015)

Integration of a Self-Organizing Map and a Virtual Pheromone for Real-Time Abnormal Movement Detection in Marine Traffic. - Julius Venskus; Povilas Treigys; Jolita Bernataviciene; Viktor Medvedev; Miroslav Voznák; Mindaugas Kurmis; Violeta Bulbenkiene (Informatica, 2017)

Real-Time Maritime Traffic Anomaly Detection Based on Sensors and History Data Embedding. - Julius Venskus; Povilas Treigys; Jolita Bernataviciene; Gintautas Tamulevicius; Viktor Medvedev (Sensors, 2019)

Investigation of Recurrent Neural Network Architectures for Prediction of Vessel Trajectory. - Robertas Jurkus; Povilas Treigys; Julius Venskus (ICIST, 2021)

Application of coordinate systems for vessel trajectory prediction improvement using a recurrent neural networks. - Robertas Jurkus; Julius Venskus; Povilas Treigys (Eng. Appl. Artif. Intell., 2023)