Results 21 to 30 of about 20,859 (261)
Refined Gate: A Simple and Effective Gating Mechanism for Recurrent Units
CoRR, 2020 Recurrent neural network (RNN) has been widely studied in sequence learning tasks, while the mainstream models (e.g., LSTM and GRU) rely on the gating mechanism (in control of how information flows between hidden states). However, the vanilla gates in RNN (e.g., the input gate in LSTM) suffer from the problem of gate undertraining, which can be caused ...
Zhanzhan Cheng +6 more
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Gated Orthogonal Recurrent Units: On Learning to Forget [PDF]
Neural Computation, 2019 We present a novel recurrent neural network (RNN)–based model that combines the remembering ability of unitary evolution RNNs with the ability of gated RNNs to effectively forget redundant or irrelevant information in its memory. We achieve this by extending restricted orthogonal evolution RNNs with a gating mechanism similar to gated recurrent unit ...
Li Jing 0001 +6 more
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Gated Recurrent Unit Network-Based Short-Term Photovoltaic Forecasting
Energies, 2018 Photovoltaic power has great volatility and intermittency due to environmental factors. Forecasting photovoltaic power is of great significance to ensure the safe and economical operation of distribution network.
Yusen Wang, Wenlong Liao, Yuqing Chang
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A simple gated recurrent network for detection of power quality disturbances
IET Generation, Transmission & Distribution, 2021 This paper presents a new concise deep learning–based sequence model to detect the power quality disturbances (PQD), which only uses original signals and does not require pre‐processing and complex artificial feature extraction process.
Xiangrong Zu, Kai Wei
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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). The most popular RNNs are Long Short-Term Memory (LSTMs), which typically reach state-of-the-art performance in many tasks thanks to their ability to learn long-term dependencies and robustness ...
Mirco Ravanelli +3 more
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IEEE Access, 2019 This paper investigates variant-gated recurrent units with encoders to preprocess packets for payload-aware intrusion detection. The variant-gated recurrent units include an encoded gated recurrent unit (E-GRU) and an encoded binarized gated recurrent ...
Yiran Hao, Yiqiang Sheng, Jinlin Wang
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Attention-Based Pose Sequence Machine for 3D Hand Pose Estimation
IEEE Access, 2020 Most of the existing methods for 3D hand pose estimation are performed from a single depth map. In that case, the depth missing challenges from input frames caused by hand self-occlusions and imaging quality lead to multi-valued mapping phenomenon and ...
Fangtai Guo +4 more
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PERBANDINGAN MODEL LSTM DAN GRU UNTUK MEMPREDIKSI HARGA MINYAK GORENG DI INDONESIA
Edusaintek, 2022 Cooking oil, a food ingredient used for cooking, has increased in price in Indonesia. Based on the Indonesian Strategic Food Price Center data, cooking oil reached twice the regular price at the beginning of 2022.
Mochammad Agus Sholeh
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Audio Captioning using Gated Recurrent Units
CoRR, 2020 Audio captioning is a recently proposed task for automatically generating a textual description of a given audio clip. In this study, a novel deep network architecture with audio embeddings is presented to predict audio captions. Within the aim of extracting audio features in addition to log Mel energies, VGGish audio embedding model is used to explore
Aysegül Özkaya Eren, Mustafa Sert
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Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation
Journal of Information Systems and Informatics, 2023 The Papuan Sentani language is spoken in the city of Jayapura, Papua. The law states the need to preserve regional languages. One of them is by building an Indonesian-Sentani Papua translation machine.
Rizkial Achmad +3 more
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