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Paralinguistic model for emotions recognition with deep neural networksIn this paper the computer paralinguistic model for emotions recognition based on deep neural
Deep Neural Networks for Emotion Recognition cell were used as models of deep neural networks. On their basis, an ensemble of neural networks
Emotions recognition in human speech with deep learning models as models of deep neural networks. An ensemble of neural networks was also built on their basis. Computer
Towards SDN-Enabled, Intelligent Intrusion Detection System for Internet of Things (IoT) results with two of our constructed models (i.e., cuBLSTM and cuGRUDNN) and current benchmark algorithms
Нейросетевой алгоритм подавления эха в условиях двойного разговора (EM, Mean-Shift, k-Means) дополнительно с двунаправленной рекуррентной нейронной сетью BLSTM.
OVERVIEW OF MODELS FOR STOCK MARKET VOLATILITY ANALYSIS AND FORECASTINGThe article discusses the phenomenon of volatility in the stock market. The most popular models
Modelica-based TCP simulationFor the study and verification of our mathematical model of telecommunication systems a discrete
Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development-Activity Relationships (Q)SAR models have been described in peer-reviewed publications; however, this way of sharing
Hybridization Method of Intelligent ModelsThe development trends of intelligent models
are generalized. The approach to systematization
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