Petro Liashchynskyi

Petro Liashchynskyi
Ternopil National Economic University · Computer Engineering (1)

PhD Student

About

6
Publications
3,323
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
6
Citations

Publications

Publications (6)
Chapter
Two paradigms have historically formed in artificial intelligence: neurocybernetics and black box cybernetics. The cybernetics of the “black box” is based on a logical approach. The rapid development of modern medicine is due to the use of technical diagnostic tools, and the use of new information technologies. Technical means of diagnosing allow y...
Article
The article analyzes and compares the architectures of generativeadversarialnetworks. These networks are based on convolu-tional neural networks that are widely used for classification problems. Convolutional networks require a lot of training data to achieve the desired accuracy. Generativeadversarialnetworks are used for the synthesis of biomedic...
Preprint
Full-text available
In this paper, we compare the three most popular algorithms for hyperparameter optimization (Grid Search, Random Search, and Genetic Algorithm) and attempt to use them for neural architecture search (NAS). We use these algorithms for building a convolutional neural network (search architecture). Experimental results on CIFAR-10 dataset further demo...
Article
Mo­dern da­ta­ba­ses of bi­ome­di­cal ima­ges ha­ve be­en in­ves­ti­ga­ted. Bi­ome­di­cal ima­ging has be­en shown to be ex­pen­si­ve and ti­me con­su­ming. A da­ta­ba­se of ima­ges of pre­can­ce­ro­us and can­ce­ro­us bre­asts "BPCI2100" was de­ve­lo­ped. The da­ta­ba­se con­sists of 2,100 ima­ge fi­les and a MySQL da­ta­ba­se of me­di­cal re­se­a...
Conference Paper
In this research study, the authors developed an adaptive method and algorithm for image pre-processing and models of convolutional neural networks for cytological and histological image classification. The computer experiments were conducted on the basis of central and graphics processors using CUDA technology. Histological and cytological images...

Network

Cited By