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Human physical activity recognition algorithm based on smartphone sensor data and convolutional neural network
Wan, Z. W.
model based on a Convolutional Neural Network (CNN) and uses the collected human action signals
Pixel level based convolutional neural networks model for robot navigation
Heger, D. A.
Pixel level based convolutional neural networks model for robot navigation
Neural network natural language processing tools for identifying personal priorities in the project performers selection in the field of smart agriculture
Polshchykov, K. A., Velikanova, A. S., Igityan, E. V.
to solving the classification problem based on the analysis of person’s text Internet traces using neural
The Multi-Objective Optimization of Complex Objects Neural Network Models
Тынченко, В. С., Тынченко, В. В., Бухтояров, В. В., Тынченко, С. В., Петровский, Э. А.
-objective optimization of the structure of a neural network model has been formalized, given its computational complexity
Agent communication method in cooperative environment based on the artificial neural networks
Protsenko, Y., Paramonov, A., Paramonov, A. I.
in this paper. An algorithm is proposed that is based in reinforcement learning and recurrent neural networks
Neural Network Recognition of Russian Noun and Adjective Cases in the Google Books Ngram Corpus
Savinkov A.V., Bochkarev V.V., Shevlyakova A.V., Khristoforov S.V.
network model was 96.45% for the nouns and 99.63% for the adjectives.
Artificial neural networks in digital antenna arrays
Kondratieva S., Ovchinnikova E., Shmachilin P., Anosova N.
of the simulation model of a beamforming scheme based on a multilayer direct distribution neural network and its
Routing Congestion Prediction in VLSI Design Using Graph Neural Networks
Saibodalov M., Karandashev I., Sokhova Z., Kocheva E., Zheludkov N.
layout design of digital blocks by applying graph neural network model. Early prediction of congestion
Emotions recognition in human speech with deep learning models
Shchetinin E.Y., Sevastianov L.A., Kulyabov D.S., Demidova A.V.
as models of deep neural networks. An ensemble of neural networks was also built on their basis. Computer
Lightweight Deep Neural Networks for Dense Crowd Counting Estimation
Sholtanyuk, S., Leunikau, A.
In this paper, productiveness problems of deep neural networks for dense crowd counting prediction

Страница 11 из 5746

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