Results 41 to 50 of about 16,939 (236)
Bidirectional LSTM-CRF Models for Sequence Tagging
CoRR, 2015 In this paper, we propose a variety of Long Short-Term Memory (LSTM) based models for sequence tagging. These models include LSTM networks, bidirectional LSTM (BI-LSTM) networks, LSTM with a Conditional Random Field (CRF) layer (LSTM-CRF) and bidirectional LSTM with a CRF layer (BI-LSTM-CRF).
Zhiheng Huang, Wei Xu 0017, Kai Yu 0001
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A Study on Sensor System Latency in VR Motion Sickness
Journal of Sensor and Actuator Networks, 2021 One of the most frequent technical factors affecting Virtual Reality (VR) performance and causing motion sickness is system latency. In this paper, we adopted predictive algorithms (i.e., Dead Reckoning, Kalman Filtering, and Deep Learning algorithms) to
Ripan Kumar Kundu +2 more
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Named Entity Recognition with Bidirectional LSTM-CNNs [PDF]
Transactions of the Association for Computational Linguistics, 2016 Named entity recognition is a challenging task that has traditionally required large amounts of knowledge in the form of feature engineering and lexicons to achieve high performance. In this paper, we present a novel neural network architecture that automatically detects word- and character-level features using a hybrid bidirectional LSTM and CNN ...
Jason P.C. Chiu, Eric Nichols
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Bidirectional LSTM approach to image captioning with scene features
, 2021 Image captioning involves generating a sentence that describes an image. More recently, it has been driven by encoderdecoder approaches where the encoder such as convolutional neural network (CNN) can extract the visual features of an image.
Davis Agughalam +5 more
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Sequential Modeling for the Recognition of Activities in Logistics
Sukkur IBA Journal of Emerging Technologies, 2021 Activity recognition is an important task in cyber physical system research and has been the focus of researchers worldwide. This paper presents a method for activity recognition in logistic operations using data from accelerometer and gyroscope sensors.
Zafi Sherhan Syed +3 more
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The Bidirectional Information Fusion Using an Improved LSTM Model [PDF]
Mobile Information Systems, 2021 The information fusion technology is of great significance in intelligent systems. At present, the modern coal-fired power plant has the fully functional sensor network. However, many data that are important for the operation of a power plant, such as the coal quality, cannot be directly obtained.
Tianwei Zheng +3 more
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A Hybrid GAS-ATT-LSTM Architecture for Predicting Non-Stationary Financial Time Series
MathematicsThis study proposes a hybrid approach to analyze and forecast non-stationary financial time series by combining statistical models with deep neural networks. A model is introduced that integrates three key components: the Generalized Autoregressive Score
Kevin Astudillo +4 more
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Bidirectional Tree-Structured LSTM with Head Lexicalization
CoRR, 2016 Sequential LSTM has been extended to model tree structures, giving competitive results for a number of tasks. Existing methods model constituent trees by bottom-up combinations of constituent nodes, making direct use of input word information only for leaf nodes.
Zhiyang Teng, Yue Zhang 0004
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Bidirectional LSTM (Bi-LSTM) network.
, 2019 Bidirectional LSTM (Bi-LSTM) network.
Yinhai Wang (182679) +4 more
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, 2023 The objective of this research is to develop an accurate gold price forecasting model using Bidirectional LSTM model, taking into account significant factors such as the SPX500 Index, USD Index, Crude Oil Prices, and Consumer Price Index (CPI ...
Leow, Meng Chew +2 more
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