Pregled bibliografske jedinice broj: 1053132
Implementation of intelligent model for pneumonia detection
Implementation of intelligent model for pneumonia detection // Tehnički glasnik - Technical journal, 13 (2019), 4; 315-322 doi:10.31803/tg-20191023102807 (recenziran, članak, znanstveni)
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Naslov
Implementation of intelligent model for pneumonia
detection
Autori
Knok, Željko ; Pap, Klaudio ; Hrnčić, Marko
Izvornik
Tehnički glasnik - Technical journal (1846-6168) 13
(2019), 4;
315-322
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
computer vision ; machine learning ; neural networks ; pneumonia
Sažetak
The advancement of technology in the field of artificial intelligence and neural networks allows us to improve speed and efficiency in the diagnosis of various types of problems. In the last few years, the rise in the field of convolutional neural networks has been particularly noticeable, showing promising results in problems related to image processing and computer vision. Given that humans have limited ability to detect patterns in individual images, accurate diagnosis can be a problem for even medical professionals. In order to minimize the number of errors and unintended consequences, computer programs based on neural networks and deep learning principles are increasingly used as assistant tools in medicine. The aim of this study was to develop a model of an intelligent system that receives x-ray image of the lungs as an input parameter and, based on the processed image, returns the possibility of pneumonia as an output. The implementation of this functionality was implemented through transfer learning methodology based on already defined convolution neural network architectures.
Izvorni jezik
Engleski
Znanstvena područja
Grafička tehnologija, Interdisciplinarne tehničke znanosti
POVEZANOST RADA
Projekti:
EK-EFRR-KK.01.1.1.02.0009 - Centar održivog razvoja (EK ) ( CroRIS)
Ustanove:
Grafički fakultet, Zagreb,
Zdravstveno veleučilište, Zagreb,
Međimursko veleučilište u Čakovcu
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)