Results 11 to 20 of about 349,230 (288)
Temporal-Kernel Recurrent Neural Networks [PDF]
Neural Networks, 2010 A Recurrent Neural Network (RNN) is a powerful connectionist model that can be applied to many challenging sequential problems, including problems that naturally arise in language and speech. However, RNNs are extremely hard to train on problems that have long-term dependencies, where it is necessary to remember events for many timesteps before using ...
Sutskever, Ilya, Hinton, Geoffrey
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Recurrent Neural Network and Auto-Regressive Recurrent Neural Network for trend prediction of COVID-19 in India [PDF]
ITM Web of Conferences, 2022 On 31st December 2019 in Wuhan China, the first case of Covid-19 was reported in Wuhan, Hubei province in China. Soon world health organization has declared contagious coronavirus disease (COVID-19) as a global pandemic in the month of March 2020.
Bouhaddour Samya +4 more
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Minute-wise frost prediction: An approach of recurrent neural networks
Array, 2022 Frost events incur substantial economic losses to farmers. These events could induce damage to plants and crops by damaging the cells. In this article, a recurrent neural network-based method, automating the frost prediction process, is proposed.
Ian Zhou +3 more
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Speech Command Recognition using Artificial Neural Networks
JOIV: International Journal on Informatics Visualization, 2020 Speech is one of the most effective way for human and machine to interact. This project aims to build Speech Command Recognition System that is capable of predicting the predefined speech commands. Dataset provided by Google’s TensorFlow and AIY teams is
Sushan Poudel, Dr. R Anuradha
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CAAI Transactions on Intelligence Technology, 2023 Manipulators actuate joints to let end effectors to perform precise path tracking tasks. Recurrent neural network which is described by dynamic models with parallel processing capability, is a powerful tool for kinematic control of manipulators.
Zhan Li, Shuai Li
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Frontiers in Human Neuroscience, 2021 It was meaningful to predict the customers' decision-making behavior in the field of market. However, due to individual differences and complex, non-linear natures of the electroencephalogram (EEG) signals, it was hard to classify the EEG signals and to ...
Qingguo Ma +7 more
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Effect of Bodybuilding and Fitness Exercise on Physical Fitness Based on Deep Learning
Emergency Medicine International, 2022 With the rapid development of society and economy, people’s living standards are improving day by day, and increasingly attention is paid to physical health, which has set off a fitness upsurge.
Manman Sun, Lijun Wang
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An attractor-based complexity measurement for Boolean recurrent neural networks. [PDF]
PLoS ONE, 2014 We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics.
Jérémie Cabessa, Alessandro E P Villa
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From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing [PDF]
, 2017 In recent studies [1][13][12] Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, data compression is also based on predictions. What the
Argerich, Luis +2 more
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Deductron—A Recurrent Neural Network
Frontiers in Applied Mathematics and Statistics, 2020 The current paper is a study in Recurrent Neural Networks (RNN), motivated by the lack of examples simple enough so that they can be thoroughly understood theoretically, but complex enough to be realistic.
Marek Rychlik
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