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По вашему запросу найдено документов: 16337

Страница 17 из 1634

Development of information system for recognizing and classifying chest pathologies

Nazarieva A.I.

of the problem of distinguishing and classifying chest pathologies using deep learning convolution of neural

Contour-aware multi-label chest X-ray organ segmentation

Kholiavchenko M., Sirazitdinov I., Kubrak K., Badrutdinova R., Kuleev R., Yuan Y., Vrtovec T., Ibragimov B.

investigated the benefits of augmenting state-of-the-art deep convolutional neural networks (CNNs) for image

A Study of the Scaling Behavior of the Two-dimensional Ising Model by Methods of Machine Learning

Chubarova, Alina A., Mamonova, Marina V., Prudnikov, Pavel V., Чубарова, Алина А., Мамонова, Марина В., Прудников, Павел В

. The method is based on a convolutional neural network (CNN) with controlled learning. The scaling functions

Developing a negative speech emotion recognition model for safety systems using deep learning

Jena S., Basak S., Agrawal H., Saini B., Gite S., Kotecha K., Alfarhood S.

the presence of the wake-up keyword 'ON' in the speech using a Convolutional Neural Network (CNN) model

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

Оценка стоимости европейского опциона при помощи нейронной сети на основе биномиального дерева

Дяченко З.К.

In this paper, the price of a European put option is estimated using an artificial neural networks

Система классификации звуков окружающей среды

Жук, И. Н., Zhuk, I. N.

architectures. Experiments based on different architectures of convolutional neural networks and proposed

Construction and efficiency analysis of neural network models for assessing the financial condition of enterprises

Ismagilov I., Molotov L., Katasev A., Kataseva D.

the problem of constructing and analyzing the effectiveness of neural network models for assessing

Improvement of 'winner takes all' neural network training for the purpose of diesel engine fault clustering

Iliukhin A., Gibadullin R.

to implement the analysis with the help of an artificial neural network. The application of the artificial

Detection of cardiac arrhythmia based on the analysis of electrocardiogram using deep learning models

Shchetinin Eugene.Yu., Sevastyanov L.A., Demidova A.V., Blinkov Y.A.

of convolutional (CNN) and recurrent deep neural networks with LSTM unit. The results of performed computer

Страница 17 из 1634

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