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description: Celem rozprawy jest przeanalizowanie problemów związanych ze stworzeniem systemu rozpoznawania obrazów. Aby nauczyć system proponowana jest metoda krokowa, gdzie w każdym etapie system uczy się na podstawie przykładów o znanych klasach, a następnie generuje przykłady trudniejsze, oceniane przez ekspertów. Praca rozpoczyna się od przeglądu zagadnień związanych z rozpoznawaniem obrazów oraz opisu progowych funkcji przełączających. Następnie opisany jest model adaptacyjnego systemu rozpoznawania obrazów MAURO. Omówiono podstawy teoretyczne, ogólną organizację systemu oraz algorytmy realizowane przez jego poszczególne bloki. Po opisie teoretycznym przedstawione są praktyczne przykłady zastosowania systemu. Pierwszy przykład dotyczy prognozowania bezpośredniego i odległego rokowania pacjentów z zawałem serca i powstał dzięki współpracy z II Kliniką Chorób Wewnętrznych Centralnego Szpitala WAM. Drugi przykład dotyczy prognozowania dydaktycznego na podstawie danych udostępnionych przez Kierownika Pracowni Metodyki Badań Socjologicznych UW. Stanowi on próbę predykcji w systemie rekrutacji na studia wyższe oraz terminowości i jakości zdawania egzaminów przez studentów pierwszych lat.
place of creation: Warszawa
scientific discipline: Dziedzina nauk inżynieryjno-technicznych / informatyka techniczna i telekomunikacja (2018)
origin: AZON2
number of pages: 242
destination group: naukowcy
title: Model adaptacyjnego systemu rozpoznawania obrazów i jego zastosowanie w prognozowaniu (PD-1973-10)

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