Vessel detection using image processing and Neural Networks

Konstantina Bereta, Raffaele Grasso & Dimitris Zissis - 2020 IEEE International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2020) - 2020


The establishment of the Automatic Identification System (AIS) was revolutionary for Maritime Situational Awareness, as it allowed for the tracking of vessels carrying an AIS transponder, which is mandatory for, and not limited to, the majority of the commercial fleet. Despite the benefits of the widespread use of AIS for...

INforE: Interactive Cross-platform Analytics for Everyone

Nikos Giatrakos; David Arnu; Theodoros Bitsakis; Antonios Deligiannakis; Minos Garofalakis; Ralf Klinkenberg; Aris Konidaris; Antonis Kontaxakis; Yannis Kotidis; Vasilis Samoladas; Alkis Simitsis; George Stamatakis; Fabian Temme; Mate Torok; Edwin Yaqub; Arnau Montagud; Miguel Ponce de León; Holger Arndt; Stefan Burkard - CIKM 2020 - 2020


We present INforE, a prototype supporting non-expert programmers in performing optimized, cross-platform, streaming analytics at scale. INforE offers: a) a new extension to the RapidMiner Studio for graphical design of Big streaming Data workflows, (b) a novel optimizer to instruct the execution of workflows across Big Data platforms and clusters,...

Automatic Maritime Object Detection Using Satellite imagery

Konstantina Bereta, Raffaele Grasso & Dimitris Zissis - IEEE Oceans 2020 - 2020


In this paper we present an approach for performing object classification and segmentation in satellite images for the Maritime domain. We employ neural network architectures for object classification and segmentation tasks in order to identify different classes of objects in satellite imagery for the maritime domain, such as vessels, land...

WOLED: A Tool for Online Learning Weighted Answer Set Rules for Temporal Reasoning Under Uncertainty

Nikos Katzouris , Alexander Artikis - Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR) - 2020


Complex Event Recognition (CER) systems detect event oc- currences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring....

Fine-Tuned Compressed Representations of Vessel Trajectories

Fikioris G., Patroumpas K., Artikis A., Paliouras G. and Pitsikalis M. - International Conference on Information and Knowledge Management (CIKM) - 2020


In the maritime domain, vessels typically maintain straight, predictable routes at open sea, except in the rare cases of adverse weather conditions, accidents and traffic restrictions. Consequently, large amounts of streaming positional updates from vessels can hardly contribute additional knowledge about their actual motion patterns. We have been developing a...

This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 825070.

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