Results 11 to 20 of about 79,032 (283)
Improving speech recognition by revising gated recurrent units [PDF]
Interspeech 2017, 2017 Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs).
Bengio, Yoshua +3 more
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Attention-enhanced gated recurrent unit for action recognition in tennis [PDF]
PeerJ Computer ScienceHuman Action Recognition (HAR) is an essential topic in computer vision and artificial intelligence, focused on the automatic identification and categorization of human actions or activities from video sequences or sensor data.
Meng Gao, Bingchun Ju
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IEEE Access, 2022 Electricity theft is considered one of the most significant reasons of the non technical losses (NTL). It negatively influences the utilities in terms of the power supply quality, grid’s safety, and economic loss.
Pamir +5 more
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Temporal action localization using gated recurrent units
The Visual Computer, 2022 Temporal Action Localization (TAL) task which is to predict the start and end of each action in a video along with the class label of the action has numerous applications in the real world. But due to the complexity of this task, acceptable accuracy rates have not been achieved yet, whereas this is not the case regarding the action recognition task. In
Keshvarikhojasteh, Hassan +2 more
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Gate-variants of Gated Recurrent Unit (GRU) neural networks [PDF]
2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 2017 The paper evaluates three variants of the Gated Recurrent Unit (GRU) in recurrent neural networks (RNN) by reducing parameters in the update and reset gates. We evaluate the three variant GRU models on MNIST and IMDB datasets and show that these GRU-RNN variant models perform as well as the original GRU RNN model while reducing the computational ...
Dey, Rahul, Salem, Fathi M.
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Research on power system fault prediction based on GA-CNN-BiGRU
Frontiers in Energy Research, 2023 Introduction: This paper proposes a power system fault prediction method that utilizes a GA-CNN-BiGRU model. The model combines a genetic algorithm (GA), a convolutional neural network (CNN), and a bi-directional gated recurrent unit network ...
Daohua Zhang +3 more
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Deep Gated Recurrent Unit for Smartphone-Based Image Captioning
Sakarya University Journal of Computer and Information Sciences, 2021 Expressing the visual content of an image in natural language form has gained relevance due to technological and algorithmic advances together with improved computational processing capacity.
Volkan Kılıç
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Minimal gated unit for recurrent neural networks [PDF]
International Journal of Automation and Computing, 2016 Recently recurrent neural networks (RNN) has been very successful in handling sequence data. However, understanding RNN and finding the best practices for RNN is a difficult task, partly because there are many competing and complex hidden units (such as LSTM and GRU).
Zhou, Guo-Bing +3 more
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Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press
Energies, 2021 The accuracy of a predictive system is critical for predictive maintenance and to support the right decisions at the right times. Statistical models, such as ARIMA and SARIMA, are unable to describe the stochastic nature of the data.
Balduíno César Mateus +4 more
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Point of Interest Recommendation Algorithm of Gated Recurrent Unit Based on Time Series and Distance [PDF]
Jisuanji gongcheng, 2020 Most Point of Interest(POI) recommendation algorithms are susceptible to the influence of time and geographical location,causing incompleteness and ambiguity in related text information of POI.Starting from the correlation between time and geographical ...
XIA Yongsheng, WANG Xiaorui, BAI Peng, LI Mengmeng, XIA Yang, ZHANG Kai
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