Open AccessNEURAL NETWORKS FROM KERAS IN SKIN LESION DIAGNOSTIC
Author(s) -
Magdalena Michalska
Publication year - 2022
Publication title -
informatyka, automatyka, pomiary w gospodarce i ochronie środowiska
Language(s) - English
Resource type - Journals
eISSN - 2391-6761
pISSN - 2083-0157
DOI - 10.35784/iapgos.2876
Subject(s) - artificial neural network , artificial intelligence , computer science , skin lesion , selection (genetic algorithm) , machine learning , process (computing) , population , pattern recognition (psychology) , dermatology , medicine , operating system , environmental health
. Melanoma is currently one of the most dangerous skin diseases, in addition many others appear in the population. Scientists are developing techniques for early non-invasive skin lesions diagnosis from dermatoscopic images, for this purpose neural networks are increasingly used. Many tools are being developed to allow for faster implementation of the network, including the Keras package. . The article presents selected methods of diagnosing skin diseases, including the process of classification, features selection, extracting the skin lesion from the whole image.The described methods have been implemented using deep neural networks available in the Keras package. The article draws attention to the effectiveness, specificity, accuracy of classification based on available data sets, attention was paid to tools that allow for more effective operation of algorithms.