Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Tomaz Martincic"'
In this paper, we present a ship detection pipeline for low-cost medium resolution satellite optical imagery obtained from ESA Sentinel-2 and Planet Labs Dove constellations. This optical satellite imagery is readily available for any place on Earth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1213f13dc59810e5a0f6ac551b30d8b4
http://arxiv.org/abs/2104.13923
http://arxiv.org/abs/2104.13923
Autor:
Clemente, Jos�� A., Mart��nez, Juli��n, Llorente, Miguel ��ngel, Torres, Ismael, Molina, Benjam��n, Fuart, Flavio, Murn, Damjan, Stepec, Dejan, Tomaz Martincic, Despland, Marc
Deliverable D6.4 is the second version of the “PIXEL data acquisition, infor mation hub and data representation” deliverable. Both deliverables are the main asset of software documentation for this project, including data sources, collecting mech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::246d1a1f0609b9e6231653e6b0726d01
https://doi.org/10.5281/zenodo.5846012
https://doi.org/10.5281/zenodo.5846012
Autor:
Molina, Benjam��n, Lacalle, Ignacio, Palau, Carlos E., Clemente, Jos�� A., Torres, Ismael, Fuart, Flavio, Murn, Damjan, Stepec, Dejan, Tomaz Martincic, Despland, Marc
Technical specification of developed methods and services. Both API and other software-related documentation will be in a standardised format permitting particular deployments to access the software adequately.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::652604c2d258b0d4a86cfe269c244b39
https://doi.org/10.5281/zenodo.5846030
https://doi.org/10.5281/zenodo.5846030
Publikováno v:
2020 21st IEEE International Conference on Mobile Data Management (MDM)
In this paper, we present a novel system for predicting vessel turnaround time, based on machine learning and standardized port call data. We also investigate the use of specific external maritime big data, to enhance the accuracy of the available da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e29ef132fffd34e2b46fd25f70cb25f
https://doi.org/10.1109/mdm48529.2020.00060
https://doi.org/10.1109/mdm48529.2020.00060
Autor:
Benjamín Molina, José A. Clemente, Flavio Fuart, Damjan Murn, Tomaz Martincic, Tim Lunar, Paolo Casoto, Charles Garnier, Romain Quéraud, Marc Despland, Olivier Le Brun, Luka Traven, Stjepan Pilicic, Teodora Milosevic, Tamara Corsano, Eleonora Anut, Cinzia Ninzatti, Christos K. Papadopoulos, Athanasios Chaldeakis, Stefano Bevilacqua, Thibault Guillon, Leonidas Pitsikas, Annie Kortsari
This document presents the results of performance, user acceptance and security evaluation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2469c61690d5a563a51cb73e852e67c3
Publikováno v:
Global Oceans 2020: Singapore – U.S. Gulf Coast
Automatic Identification System (AIS) data represents a rich source of information about maritime traffic and offers a great potential for data analytics and predictive modeling solutions, which can help optimizing logistic chains and to reduce envir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3107cf6b71ff134265b96fba9512a9f5