Results 141 to 150 of about 5,130 (182)

Bidirectional GRU with Multi-Head Attention for Chinese NER

2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC), 2020
Named entity recognition (NER) is a basic task of natural language processing (nlp), which purpose is to locate the named entities in natural language text, and classify them into predefined categories such as persons (PER), locations (LOC), and organizations (ORG).
Shuo Yan, Jianping Chai, Liyun Wu
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Bidirectional GRU networks‐based next POI category prediction for healthcare

International Journal of Intelligent Systems, 2021
The Corona Virus Disease 2019 has a great impact on public health and public psychology. People stay at home for a long time and rarely go out. With the improvement of the epidemic situation, people began to go to different places to check in. To maintain public mental health, it is necessary to propose a point-of-interest (POI) prediction model which ...
Yuwen Liu 0003, Zuolong Song, Xiaolong Xu 0001, Wajid Rafique, Xuyun Zhang, Jun Shen 0001, Mohammad Reza Khosravi, Lianyong Qi   +7 more
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Arabic Named Entity Recognition: A Bidirectional GRU-CRF Approach

2018
The previous Named Entity Recognition (NER) models for Modern Standard Arabic (MSA) rely heavily on the use of features and gazetteers, which is time consuming. In this paper, we introduce a novel neural network architecture based on bidirectional Gated Recurrent Unit (GRU) combined with Conditional Random Fields (CRF).
Mourad Gridach, Hatem Haddad
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An explainable attention-based bidirectional GRU model for pedagogical classification of MOOCs

Interactive Technology and Smart Education, 2022
Purpose The purpose of this study is, First, to leverage the limitation of annotated data and to identify the cognitive level of learning objectives efficiently, this study adopts transfer learning by using word2vec and a bidirectional gated recurrent units (GRU) that can fully take into account the context and improves the classification of the model.
Hanane Sebbaq, Nour-Eddine El Faddouli
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Accurate Heart Beat Detection with Doppler Radar using Bidirectional GRU Network

2023 IEEE Radio and Wireless Symposium (RWS), 2023
Heart rate is one of the most critical and important vital signs in healthcare. While electrocardiography (ECG) is gold-standard procedure for heart rate monitoring, contactless monitoring is preferred in many applications like long-term monitoring. Radar systems enable contactless sensing by measuring small movements on the chest induced by the heart ...
Hui Lu, Markus Heyder, Marvin Wenzel, Nils C. Albrecht, Dominik Langer, Alexander Koelpin   +5 more
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The LSTM and Bidirectional GRU Comparison for Text Classification

2023
Although the phrases machine learning and AI are frequently used interchangeably and are frequently discussed together, they do not have the same meanings. While all artificial intelligence (AI) is machine learning, not all AI is machine learning, which is a key distinction.
Asrawi, Hannan, Utami, Ema, Yaqin, Ainul
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An efficient stacked bidirectional GRU‐LSTM network for intracranial hemorrhage detection

International Journal of Imaging Systems and Technology, 2023
Abstract Intracranial hemorrhage (ICH) is a dangerous condition that needs prompt diagnosis and treatment. Computed tomography (CT) images are employed in examination of individuals with ICH, which produces better results and cost‐effective than MRI.
Lakshmi Prasanna Kothala, Sitaramanjaneya Reddy Guntur   +1 more
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Opinion Expression Detection via Deep Bidirectional C-GRUs

2017 28th International Workshop on Database and Expert Systems Applications (DEXA), 2017
The ability to accurately detect opinion expression in a document is an essential and fundamental task in opinion mining. In this work, we consider opinion expression detection as a sequence labeling task. We describe deep neural network frameworks that consist of convolutional neural networks (CNNs) and bidirectional gated units (Bi-GRUs).
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Chinese Word Segmentation based on Bidirectional GRU-CRF Model

International Journal of Performability Engineering, 2018
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Bidirectional-GRU Based on Attention Mechanism for Aspect-level Sentiment Analysis

Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019
Aspect-level sentiment analysis is a fine-grained natural language processing task. For traditional deep learning models, they cannot accurately construct the aspect-level sentiment features. Such as, for the sentence of "the movie is very funny, but the seats in the theater is uncomfortable." For the movie, the polarity is positive, but it is negative
Penghua Zhai, Dingyi Zhang
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