Results 21 to 30 of about 312,321 (283)
Medical Image Interpolation Using Recurrent Type-2 Fuzzy Neural Network
Frontiers in Neuroinformatics, 2021 Image interpolation is an essential process for image processing and computer graphics in wide applications to medical imaging. For image interpolation used in medical diagnosis, the two-dimensional (2D) to three-dimensional (3D) transformation can ...
Jafar Tavoosi +5 more
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Journal of Advances in Modeling Earth Systems, 2023 Systematic biases in numerical weather prediction models cause forecast deviation from reality. While model biases also affect data assimilation and degrade the analysis accuracy, observation information incorporated through data assimilation can provide
A. Amemiya, M. Shlok, T. Miyoshi
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IEEE Access, 2022 In this paper, a class of Clifford-valued neutral-type recurrent neural networks with $D$ operator is explored. By using non-decomposition method and the Banach fixed point theorem, we obtain several sufficient conditions for the existence of anti ...
Jin Gao, Lihua Dai
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Engineering Proceedings, 2023 Artificial neural networks with different structures are used for identification of complex dynamic plant with distributed parameters. The plant is a high-temperature plasma in the spherical Globus-M2 tokamak.
Valerii I. Kruzhkov +2 more
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Random Recurrent Neural Networks Dynamics [PDF]
, 2006 This paper is a review dealing with the study of large size random recurrent neural networks. The connection weights are selected according to a probability law and it is possible to predict the network dynamics at a macroscopic scale using an averaging ...
Cessac, B., Samuelides, M.
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Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
IEEE Access, 2021 A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design ...
Kaisheng Liao +4 more
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Echo state networks as an alternative to traditional artificial neural networks in rainfall–runoff modelling [PDF]
Hydrology and Earth System Sciences, 2013 Despite theoretical benefits of recurrent artificial neural networks over their feedforward counterparts, it is still unclear whether the former offer practical advantages as rainfall–runoff models.
N. J. de Vos
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Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition
Frontiers in Psychology, 2017 Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in
Courtney J. Spoerer +2 more
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SHS Web of Conferences, 2018 The problems of applying neural network methods for solving problems of preventing cyberthreats to flexible self-organizing network infrastructures of digital economy platforms: vehicle adhoc networks, wireless sensor networks, industrial IoT, “smart ...
Kalinin Maxim +2 more
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Sensors, 2023 This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to
Francisco Rau +6 more
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