Optimal initialization of neural networks

dc.contributor.advisor	Крюкова, Галина
dc.contributor.author	Кузьменко, Дмитро
dc.date.accessioned	2020-11-11T19:14:59Z
dc.date.available	2020-11-11T19:14:59Z
dc.date.issued	2020
dc.description.abstract	Artificial neural networks have seen a big surge in popularity. The reason for that is the fact that a lot of different areas, such as photo/video – oriented tasks (object detection, object recognition, semantic segmentation, bounding boxes etc.), neural machine translation, optical character recognition, automated driving and many others, are at the moment the best application of such an approach. Moreover, the use of so called “deep” neural networks is getting widely known now. While having both the computational power increase (modern GPUs are helping with the matter) and the access to enormous amounts of data pushes machine learning engineers and researchers to give up the idea of shallow networks (the ones that have few layers).	uk_UA
dc.identifier.uri	https://ekmair.ukma.edu.ua/handle/123456789/18590
dc.language.iso	en	uk_UA
dc.status	first published	uk_UA
dc.subject	neural networks	uk_UA
dc.subject	optimal initialization	uk_UA
dc.subject	комп'ютерне забезпечення	uk_UA
dc.subject	програмування	uk_UA
dc.subject	курсова робота	uk_UA
dc.title	Optimal initialization of neural networks	uk_UA
dc.type	Other	uk_UA

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