Results 31 to 40 of about 16,939 (236)
DG-based SPO tuple recognition using self-attention M-Bi-LSTM
ETRI Journal, 2022 This study proposes a dependency grammar-based self-attention multilayered bidirectional long short-term memory (DG-M-Bi-LSTM) model for subject?predicate?object (SPO) tuple recognition from natural language (NL) sentences. To add recent knowledge to the
Joon-young Jung
doaj +1 more source
Applied Sciences, 2023 Recently, neural network technology has shown remarkable progress in speech recognition, including word classification, emotion recognition, and identity recognition. This paper introduces three novel speaker recognition methods to improve accuracy.
Young-Long Chen +3 more
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Unidirectional and Bidirectional LSTM Models for Short-Term Traffic Prediction
, 2021 This paper presents the development and evaluation of short-term traffic prediction models using unidirectional and bidirectional deep learning long short-term memory (LSTM) neural networks.
Rusul L. Abduljabbar +2 more
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Early Action Prediction using 3DCNN with LSTM and Bidirectional LSTM
Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021 Predicting and identifying suspicious activities before hand is highly beneficial because it results in increased protection in video surveillance cameras’. Detecting and predicting human's action before it is carried out has a variety of uses like autonomous robots, surveillance, and health care. The main focus of the paper is on automated recognition
Manju D, Dr. Seetha M., Dr. Sammulal P.
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Heart Sound Segmentation Using Bidirectional LSTMs With Attention [PDF]
IEEE Journal of Biomedical and Health Informatics, 2020 This paper proposes a novel framework for the segmentation of phonocardiogram (PCG) signals into heart states, exploiting the temporal evolution of the PCG as well as considering the salient information that it provides for the detection of the heart state.
Tharindu Fernando +5 more
openaire +4 more sources
Applied Sciences, 2020 Accurate estimation of reference evapotranspiration (ETo) provides useful information for water resource management and sustainable agriculture. This study estimates ETo with recurrent neural networks (RNNs), namely long short-term memory (LSTM) and ...
Hassan Afzaal +4 more
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LSTM-based Multi-Step SOC Forecasting of Battery Energy Storage in Grid Ancillary Services
, 2021 Battery energy storage (BES) participation in the grid ancillary services markets is increasing rapidly in recent years. To facilitate optimal participation, the need for accurate BES state-of-charge (SOC) forecasting is indispensable.
Ardiansyah Ardiansyah (11241801) +2 more
core +1 more source
Multi‐step‐ahead flood forecasting using an improved BiLSTM‐S2S model
Journal of Flood Risk Management, 2022 Rainfall–runoff modeling is a complex hydrological issue that still has room for improvement. This study developed a coupled bidirectional long short‐term memory (LSTM) with sequence‐to‐sequence (Seq2Seq) learning (BiLSTM‐Seq2seq) model to simulate multi‐
Qing Cao +4 more
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An Attention-based Bidirectional LSTM Model for Continuous Cross-subject Estimation of Knee Joint Angle during Running from sEMG Signals [PDF]
, 2023 Running is an essential locomotion activity that plays a critical role in everyday life and exercise activities and may be impeded by joint disease and neurological impairments.
Zangene, Alireza Rezaie +11 more
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Ship Roll Prediction Algorithm Based on Bi-LSTM-TPA Combined Model
Journal of Marine Science and Engineering, 2021 When ships sail on the sea, the changes of ship motion attitude presents the characteristics of nonlinearity and high randomness. Aiming at the problem of low accuracy of ship roll angle prediction by traditional prediction algorithms and single neural ...
Yuchao Wang +3 more
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