WIELOKLASOWA KLASYFI KACJA Z NAM ION SK Ó RNYCH W OPARCIU O GŁĘBOKIE SIECI NEURONOW E

Magdalena Michalska

mmagamichalska@gmail.com
Politechnika Lubelska, Katedra Elektroniki i Technik Informacyjnych (Polska)
http://orcid.org/0000-0002-0874-3285

Abstrakt

Choroby skóry diagnozowane za pomocą dermatoskopii są coraz powszechniejsze. Wykorzytanie skomputeryzowanych systemów diagnostyki staje się niezwykle skuteczne. Nieiwazyjne metody diagnostyki, jakimi są głębokie sieci neuronowe są coraz powszechniejszym narzędziem badanym przez naukowców. W artykule przedstawiono przegląd wybranych głównych zagadnień związanych w procesem klasyfikacji wieloklasowej: etap wyboru bazy danych, wstępnego przetwarzania obrazów, doboru zestawu danych uczących, narzędzi klasyfikacji, etapu trenowania sieci i otrzymania wyników końcowych. Opisane działania zostały zaimplementowane za pomocą dostępnych głębokich sieci neuronowych. W artykule zwrócono uwagę na wyniki końcowe dostępnych modeli, takich jak skuteczność, specyficzność, dokładność klasyfikacji dla różnej ilości klas i dostępnych zestawów danych.


Słowa kluczowe:

obrazy dermatoskopowe, wieloklasowa klasyfikacja, zmiany skórne, głębokie sieci neuronowe

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Opublikowane
2022-06-30

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Michalska, M. (2022). WIELOKLASOWA KLASYFI KACJA Z NAM ION SK Ó RNYCH W OPARCIU O GŁĘBOKIE SIECI NEURONOW E . Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 12(2), 10–14. https://doi.org/10.35784/iapgos.2963

Autorzy

Magdalena Michalska 
mmagamichalska@gmail.com
Politechnika Lubelska, Katedra Elektroniki i Technik Informacyjnych Polska
http://orcid.org/0000-0002-0874-3285

Statystyki

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