Spoken Language Identification System Using Convolutional Recurrent Neural Network
Applied Sciences, 2022 Following recent advancements in deep learning and artificial intelligence, spoken language identification applications are playing an increasingly significant role in our day-to-day lives, especially in the domain of multi-lingual speech recognition. In
Adal A. Alashban +3 more
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Recurrent Convolutional Neural Network for Sequential Recommendation
The World Wide Web Conference, 2019 The sequential recommendation, which models sequential behavioral patterns among users for the recommendation, plays a critical role in recommender systems. However, the state-of-the-art Recurrent Neural Networks (RNN) solutions rarely consider the non-linear feature interactions and non-monotone short-term sequential patterns, which are essential for ...
Chengfeng Xu +7 more
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Spatiotemporal Graph Convolutional Recurrent Neural Network Model for Citywide Air Pollution Forecasting [PDF]
arXiv.org, 2021 This paper applies a Spatiotemporal Graph Convolutional Recurrent Neural Network which is a tight combination of a Graph Neural Network (GNN) to a Recurrent Neural Network (RNN) architecture for air pollution forecasting in long-term for the entire city.
Van-Duc Le
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Journal of King Saud University: Computer and Information Sciences, 2022 Sentiment analysis has been a well-studied research direction in computational linguistics. Deep neural network models, including convolutional neural networks (CNN) and recurrent neural networks (RNN), yield promising results on text classification ...
Aytuğ Onan
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Convolutional Neural Networks with Gated Recurrent Connections [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 The convolutional neural network (CNN) has become a basic model for solving many computer vision problems. In recent years, a new class of CNNs, recurrent convolution neural network (RCNN), inspired by abundant recurrent connections in the visual systems of animals, was proposed.
Jianfeng Wang, Xiaolin Hu 0001
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Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for Short-Term Forecasting of Transit Passenger Flow [PDF]
IEEE transactions on intelligent transportation systems (Print), 2021 Short-term forecasting of passenger flow is critical for transit management and crowd regulation. Spatial dependencies, temporal dependencies, inter-station correlations driven by other latent factors, and exogenous factors bring challenges to the short ...
Yuxin He +3 more
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Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting [PDF]
IEEE transactions on intelligent transportation systems (Print), 2018 Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due to the time-varying traffic patterns and the complicated spatial dependencies on road networks.
Zhiyong Cui +3 more
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Parralel Recurrent Convolutional Neural Network for Abnormal Heart Sound Classification [PDF]
, 2023 This paper presents the results of a study performed on Parallel Convolutional Neural Network (PCNN) toward detecting heart abnormalities from the heart sound signals.
Gharehbaghi, Arash, +5 more
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Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting [PDF]
International Joint Conference on Artificial Intelligence, 2017 Timely accurate traffic forecast is crucial for urban traffic control and guidance. Due to the high nonlinearity and complexity of traffic flow, traditional methods cannot satisfy the requirements of mid-and-long term prediction tasks and often neglect ...
Ting Yu, Haoteng Yin, Zhanxing Zhu
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Convolutional recurrent neural networks for music classification [PDF]
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 5 pages, ICASSP 2017 submitted.
Keunwoo Choi +3 more
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