Е-Публикации
Технически университет - София

Abstract: In recent years, the algorithms of artificial intelligence (AI) are being developed extensively and they attract increasing attention of scientists since they open doors to efficient solutions of many problems that otherwise require a lot of time, effort, expenses and often inspiration. A main challenge to their wider application in biophotonics is the lack of ample amount of diverse and representative data for training. Therefore, we present here the application of Neural Network (NN) algorithms trained with insufficient data for solving two biophotonics tasks. The first one is classification of Laser-Induced Fluorescence (LIF) and reflection spectra of human skin (i.e. optical biopsy) for the purpose of early and non-invasive diagnosis of skin diseases. The second one is related to verification of food quality, and more specifically the identification of mixtures of sunflower and extra virgin olive oils with different concentrations, which can be treated both as a classification and

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