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Projected Minimal Gated Recurrent Unit for Speech Recognition [PDF]
IEEE Access, 2020 Recurrent neural network (RNN) has the ability to learn long-term dependencies, which makes it suitable for acoustic modeling in speech recognition. In this paper, we revise RNN model used in acoustic modeling, namely, mGRUIP with Context module (mGRUIP ...
Renjian Feng +4 more
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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).
Guo-Bing Zhou +2 more
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A Quaternion Gated Recurrent Unit Neural Network for Sensor Fusion
Information, 2021 Recurrent Neural Networks (RNNs) are known for their ability to learn relationships within temporal sequences. Gated Recurrent Unit (GRU) networks have found use in challenging time-dependent applications such as Natural Language Processing (NLP ...
Uche Onyekpe +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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A Bayesian Interpretation of the Light Gated Recurrent Unit [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 We summarise previous work showing that the basic sigmoid activation function arises as an instance of Bayes’s theorem, and that recurrence follows from the prior. We derive a layerwise recurrence without the assumptions of previous work, and show that it leads to a standard recurrence with modest modifications to reflect use of log-probabilities.
Alexandre Bittar, Philip N. Garner
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Gated Recurrent Unit for Video Denoising
CoRR, 2022 5 pages, 5 ...
Kai Guo, Seungwon Choi, Jongseong Choi
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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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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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On the stability properties of Gated Recurrent Units neural networks [PDF]
Systems & Control Letters, 2021 The goal of this paper is to provide sufficient conditions for guaranteeing the Input-to-State Stability (ISS) and the Incremental Input-to-State Stability (δISS) of Gated Recurrent Units (GRUs) neural networks. These conditions, devised for both single-layer and multi-layer architectures, consist of nonlinear inequalities on network's weights.
Bonassi F., Farina M., Scattolini R.
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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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