Pregled bibliografske jedinice broj: 1270528
AN INNOVATIVE FRAMEWORK FOR SUPPORTING BIG-MOVING- OBJECTS TRACKING, ANALYSIS AND MINING EFFECTIVELY AND EFFICIENTLY
AN INNOVATIVE FRAMEWORK FOR SUPPORTING BIG-MOVING- OBJECTS TRACKING, ANALYSIS AND MINING EFFECTIVELY AND EFFICIENTLY // Journal of Data Intelligence, 4 (2023), 149-164 doi:10.26421/JDI4.1-2-3 (međunarodna recenzija, članak, znanstveni)
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Naslov
AN INNOVATIVE FRAMEWORK FOR SUPPORTING BIG-MOVING-
OBJECTS TRACKING, ANALYSIS AND MINING EFFECTIVELY
AND EFFICIENTLY
Autori
Cuzzocrea, Alfredo ; Gallo, Carmine ; Mumolo, Enzo ; Lenac, Kristijan
Izvornik
Journal of Data Intelligence (2577-610X) 4
(2023);
149-164
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Moving Objects ; Scan-Matching Algorithms ; Intelligent Systems ; Genetic Optimization
Sažetak
Big moving objects arise as a novel class of big data objects in emerging environments. Here, the main problems are the following: (i) tracking, which represents the baseline operation for a plethora of higher-level functionalities, such as detection, classification, and so forth ; (ii) analysis, which meaningfully marries with big data analytics scenarios. In line with these goals, in this paper we propose a novel family of scan matching algorithms based on registration, which are enhanced by using a genetic pre-alignment phase based on a novel metrics, fist, and, second, performing a finer alignment using a deterministic approach.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-295 - Ugradbeni sustavi za 3D percepciju (Lenac, Kristijan, NadSve ) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka
Profili:
Kristijan Lenac
(autor)
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