Κατηγοριοποίηση κινούμενων αντικειμένων βάσει σημασιολογικά επαυξημένων συνόψεων
Classification of moving objects based on semantically enriched synopses
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Abstract
Development in the field of information and communication technology, especially in mobile telephony detection and wireless communication, floods us with data containing geographical locations that vary over time. Although this type of data is also associated with challenges such as depletion of storage capacity and data bandwidth, researchers have shown that these data sets are a valuable resource. Their analysis can lead to solutions to important research problems in various fields, such as urban planning, transportation, ecological behavior, sports scene analysis, monitoring and security.
This thesis attempts to analyze and classify kinetic data with the help of Machine Learning algorithms. Bibliographic techniques dealing with this issue are presented, as well as definitions and handling of data that is important to the facilitator so that he can provide information on the issue. In addition, the MasterMovelets (Ferrero et al., 2020) method is presented which was used for the needs of the experimental part of the work.
Postgraduate Studies Programme
Εφαρμοσμένη ΣτατιστικήDepartment
Σχολή Χρηματοοικονομικής και Στατιστικής. Τμήμα Στατιστικής και Ασφαλιστικής ΕπιστήμηςNumber of pages
88Language
GreekCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα