Материалов:
1 005 012

Репозиториев:
30

Авторов:
761 409

По вашему запросу найдено документов: 16337

Страница 23 из 1634

Image-generating neural networks: perspectives and artists’ concerns
Samsonchyk, A. I.
The article discusses the recent development tendencies of AI and Neural Network technologies
Ensembles of neural network for telemetry multivariate time series forecasting
Doudkin, A. A., Marushko, E. E.
data using neural network ensembles. Approaches to the forming neural network ensembles are analyzed
Ensembles of neural network for telemetry multivariate time series forecasting
Doudkin, A. A., Marusko, E. E.
series of telemetry data using ensemble neural networks. Approaches to the construction of neural network
A classification of meteor radio echoes based on artificial neural network
© by Mikhail Danilov, Arkadi Karpov, published by De Gruyter 2018. An artificial neural network
Exponential Discretization of Weights of Neural Network Connections in Pre-Trained Neural Networks
Malsagov M.Y., Khayrov E.M., Pushkareva M.M., Karandashev I.M.
algorithms we consider a weight discretization problem for trained neural networks. We show
APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN CHEMICAL PROBLEMS
Бондарчук А., Зиманкова А.
The article is devoted to the Artificial Neural Networks and and their application in chemistry
Methodics and tools of cough sound processing on basic of neural net
Vishniakou, U. А., Shaya, B. H.
based on a deep neural network. Four types of machine learning and the use of convolutional neural
Assessment of technical condition of polyurethane foam thermal insulation pipelines of heating networks using neural network technologies
of research using acoustic methods, using neural network technologies to process acoustic signals. The article
Neural network model for detecting network scanning attacks
Panischev O.Y., Makridin A.T., Katasev A.S., Akhmetvaleev A.M., Kataseva D.V.
to use a trained neural network as a tool for detecting network scanning attacks. The implementation
Классификация режимов многофазных течений методами нейросетевого анализа
Пурицкис, Я. В., Вершинин, В. Е., Puritskis, Ya. V., Vershinin, V. E.
the type of flow using artificial convolutional neural networks. This approach allows you to get rid

Страница 23 из 1634

Фасеты

Новости проекта

Новости

Партнеры

КФУ
ТГУ
Elpub
СФУ
Webpublishers

Индексация

BASE
WorldCat
OpenAIRE
EDS
core