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Session:   Artificial Intelligence & Machine Learning for Ocean & Great Lakes 1
Day:   Tuesday, September 30
Time:   1:30 PM - 3:00 PM
Room:   311  

PAPERS

 
Presenting Author:   Feifei ZhouBeijing University of Chemical Technology
Paper Title:   VMD-Assisted Multi-Feature BiLSTM based Marine Traffic Flow Prediction
 
Author(s):   Feifei Zhou, Beijing University of Chemical Technology
Xiangling Li, Beijing University of Chemical Technology
Fengyuan Zhang, Beijing University of Chemical Technology

 
 
Presenting Author:   Yuchou ChangUniversity of Massachusetts Dartmouth
Paper Title:   Hybrid LIF-Izhikevich Spiking Neural Network Model for Oceanographic Data Analysis
 
Author(s):   Yuchou Chang, University of Massachusetts Dartmouth
Alissa Kane, University of Massachusetts Dartmouth
Anton Spirkin, US Naval Undersea Warfare Center Division Newport
Felipe Marcelino, US Naval Undersea Warfare Center Division Newport

 
 
Presenting Author:   Wei-Cheng ChenDepartment of Hydraulic and Ocean Engineering, National Cheng Kung University
Paper Title:   Forecast of Hazardous Sea Conditions
 
Author(s):   Wei-Cheng Chen, Department of Hydraulic and Ocean Engineering, National Cheng Kung University
Dong-Jiing Doong, Department of Hydraulic and Ocean Engineering, National Cheng Kung University
Ying-Chih Chen, Coastal Ocean Monitoring Center, National Cheng-Kung University
Chi-Hao Chu, Marine Meteorology and Climate Division, Central Weather Administration
Fang-Ru Lin, Marine Meteorology and Climate Division, Central Weather Administration

 
 
Presenting Author:   Alan HunterUniversity of Bath
Paper Title:   COLREG-Compliant Machine Learning for Safe and Legal Autonomous Maritime Navigation
 
Author(s):   Alfie Anthony Treloar, University of Bath
Dany Varghese, University of Surrey
Shubhi Verma, University of Surrey
Alireza Tamaddoni-Nezhad, University of Surrey
Alan Hunter, University of Bath

 
 
Presenting Author:   Pavly SalehUniversity of Ottawa
Paper Title:   Navigating the Annotation Bottleneck: Active Learning for Scalable Maritime Data Analytics
 
Author(s):   Pavly Saleh, University of Ottawa
John Armitage, Larus Technologies
Phillip Curtis, Larus Technologies
Rami Abielmona, Larus Technologies
Emil Petriu, University of Ottawa

 
 
Presenting Author:   Anna HuUniversity of Georgia
Paper Title:   Evaluation of a machine learning-based algorithmic pipeline for real-time onboard removal of glider self-noise from passive acoustic data
 
Author(s):   Anna Hu, University of Georgia
Aiden Gray, Washington and Lee University, Skidaway Institute of Oceanography/University of Georgia
Guoming Li, University of Georgia
Erin Meyer-Gutbrod, University of South Carolina
Catherine Edwards, Skidaway Institute of Oceanography/University of Georgia