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Exploring convolutional neural networks and topic models for user profiling from drug reviews
Tutubalina E., Nikolenko S.
processing techniques, including extensions of topic models and convolutional neural networks (CNN). We apply
Machine Learning Methods and Models for Recognizing Lung Inhomogeneity from Computed Tomography Scans
Shakhmametova, G. R., Stepanova, E. S., Akhmetshin, A. A., Zulkarneev, R. Kh.
the recognition stage, a lightweight convolutional neural network (CNN) is used. The developed approach provides
Convolutional Neural Networks for the Segmentation of Multispectral Earth Remote Sensing Images
Vinogradov A.N., Tishchenko I.P., Ivanov E.S.
of Earth remote sensing using convolutional neural networks (CNN). Various modern algorithms
Image Semantic Segmentation Based on High-Resolution Networks for Monitoring Agricultural Vegetation
Ganchenko, V., Starovoitov, V., Xiangtao Zheng
convolutional neural networks. Two variants of High-Resolution network architecture (HRNet) are described
Efficient Convolutional Neural Network-Based Keystroke Dynamics for Boosting User Authentication
AbdelRaouf H., Chelloug S.A., Muthanna A., Semary N., Amin K., Ibrahim M.
an optimized convolutional neural network that is designed to extract improved features by utilizing data
Neural networks fundamentals
Shmargun, A. E.
is provided in this paper. Neural networks and their various categories, such as Feedforward, Recurrent
UNetX: Real-time Pedestrian Crosswalk Segmentation on Mobile Device
Adaska, E., Lechanka, A.
with depthwise separable convolution ones. This neural network was trained and tested against a set of manually
Paralinguistic model for emotions recognition with deep neural networks
Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Ayrjan E.A., Demidova A.V.
convolutional networks and recurrent networks with LSTM memory cell were used. Intensive computer experiments
Classification of medical images of patients with Covid-19 using transfer learning technology of convolutional neural network
Miroshnichenko A. S.
of a healthy person and with the presence of COVID-19. The method is a trainable convolutional neural
On the Classification of Cytological Images of Leukocytes Using Depthwise Separable Convolutional Neural Networks
Shchetinin E.Yu., Glushkova A.G., Demidova A.V., Sevastianov L.A.
images, LeucoCyteNetv2, is proposed, which includes depthwise separable convolutional layers, Separable

Страница 6 из 1634

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