Results 21 to 30 of about 92,175 (266)
Recurrent Neural Network Grammars [PDF]
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016 We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling. Experiments show that they provide better parsing in English than any single previously published supervised generative model and better
Dyer, Chris +3 more
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Restricted Recurrent Neural Networks [PDF]
2019 IEEE International Conference on Big Data (Big Data), 2019 Recurrent Neural Network (RNN) and its variations such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), have become standard building blocks for learning online data of sequential nature in many research areas, including natural language processing and speech data analysis.
Enmao Diao, Jie Ding 0002, Vahid Tarokh
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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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Comparison of Neural Network and Recurrent Neural Network to Predict Rice Productivity in East Java
JITeCS (Journal of Information Technology and Computer Science), 2021 Rice is the staple food for most of the population in Indonesia which is processed from rice plants. To meet the needs and food security in Indonesia, a prediction is required.
Andi Hamdianah +2 more
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