Parallelization of convolutional neural networks based on graphics processors
Keywords:
convolutional neural networks, graphics processor, machine learning, artificial intelligence
Abstract
The paper classified and investigated the parallelization of learning algorithms of neural networks using technologies that allow the use of graphics processors to process a large amount of input data. Acceleration of the process of analysis of biomedical images by convolutional neural networks makes it possible to diagnose any deviations in human health in a short period of time. This makes it possible to detect diseases in the early stages and carry out treatment to prevent their spread.
References
1. What is artificial neural network (ANN)? [Електронний ресурс]
2. Розенблатт Ф. Принципы нейродинамики. Перйептроны и теория механизмов мозга / Ф. Розенблат. – М.: Мир, 1965. – 175с.
3. Minsky M. L. Perceptrons / Minsky M. L. Papert S. A. – Cambridge, MA: MIT Press, 1969.
4. Werbos, P.J. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences [Електронний ресурс]
5. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Rumelhart, D.E; McClelland, James / Cambridge: MIT Press. ISBN 978-0- 262-63110-5, 1986 – 567c.
2. Розенблатт Ф. Принципы нейродинамики. Перйептроны и теория механизмов мозга / Ф. Розенблат. – М.: Мир, 1965. – 175с.
3. Minsky M. L. Perceptrons / Minsky M. L. Papert S. A. – Cambridge, MA: MIT Press, 1969.
4. Werbos, P.J. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences [Електронний ресурс]
5. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Rumelhart, D.E; McClelland, James / Cambridge: MIT Press. ISBN 978-0- 262-63110-5, 1986 – 567c.
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Published
2023-12-16
How to Cite
Chernyashchuk, N., Semenyuk , V., Shabovskyi , M., Tokar , O., & Overchuk , N. (2023). Parallelization of convolutional neural networks based on graphics processors. COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, (53), 257-262. https://doi.org/10.36910/6775-2524-0560-2023-53-39
Section
Computer science and computer engineering