Deep learning based approaches for hard and soft data fusion towards better maritime domain awareness

In this project, we apply deep learning methods to analyze and obtain useful information from text data that are collected from social media, and combine these information with numerical data from physical sensors. We then develop new deep learning based solutions that exploit the combined data in order to track the ships in the open sea with more accuracy. The primary strength of our work is that social media data provides additional information when the usual physical sensors like radars and satellites can not provide enough data. Our work is integrated into the partner organization’s commercial software to illustrate the improved performance of ship tracking.

Intern: 
Moslem Ouled Sghaier;Jun Ye Yu;Zofia Grabowiecka
Superviseur universitaire: 
Jiri Patera
Province: 
Quebec
Partner University: 
Programme: