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Multimodal Object Classification Using Bidirectional Gated Recurrent Unit Networks
2018 IEEE Third International Conference on Data Science in Cyberspace (DSC), 2018In the field of artificial intelligence, we have observed a strong trend towards introducing external resources to aid pattern recognition tasks. In this work, we utilize external meta-data in the form of web text, i.e. natural language, to aid image classification.
Dongzhe Wang, Kezhi Mao
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Hate Speech Detection in Indonesian Twitter Texts using Bidirectional Gated Recurrent Unit
2021 13th International Conference on Knowledge and Smart Technology (KST), 2021As the number of social media users rises, the probability of hate speech spread in social media also rises indirectly. Hate speech has become one of most common cases found on social media. The spread of hate speech can lead to a riot that might cause conflict, group extermination, and even human casualties.
Angela Marpaung +2 more
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Labanotation Generation Based on Bidirectional Gated Recurrent Units with Joint and Line Features
2019 IEEE International Conference on Image Processing (ICIP), 2019Labanotation is an effective carrier for recording and displaying three-dimensional human movements. In the existing methods of Labanotation generation, the spatial characteristics are not fully considered. In addition, Long-term correlation of time series is not reflected. In this paper, we propose a novel method based on Bidirectional Gated Recurrent
Shanshan Hao +4 more
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Bidirectional Gated Recurrent Units For Human Activity Recognition Using Accelerometer Data
2019 IEEE SENSORS, 2019Human activity recognition aims to detect the type of human movement based on sensor data gathered during human activity. Time series classification using deep learning approaches offers opportunities to avoid intensive handcrafted feature extraction techniques where the efficiency and the accuracy are heavily dependent on the quality of variables ...
Tamam Alsarhan +3 more
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Deep Bidirectional Gated Recurrent Unit for Botnet Detection in Smart Homes
2021Bidirectional gated recurrent unit (BGRU) can learn hierarchical feature representations from both past and future information to perform multi-class classification. However, its classification performance largely depends on the choice of model hyperparameters. In this paper, we propose a methodology to select optimal BGRU hyperparameters for efficient
Segun I. Popoola +3 more
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ACM Transactions on Asian and Low-Resource Language Information Processing, 2021
For English toxic comment classification, this paper presents the model that combines Bi-GRU and CNN optimized by global average pooling (BG-GCNN) based on the bidirectional gated recurrent unit (Bi-GRU) and global pooling optimized convolution neural network (CNN) .
Zhongguo Wang, Bao Zhang
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For English toxic comment classification, this paper presents the model that combines Bi-GRU and CNN optimized by global average pooling (BG-GCNN) based on the bidirectional gated recurrent unit (Bi-GRU) and global pooling optimized convolution neural network (CNN) .
Zhongguo Wang, Bao Zhang
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Attention-based bidirectional gated recurrent unit neural networks for sentiment analysis
Proceedings of the 2nd International Conference on Artificial Intelligence and Pattern Recognition, 2019Sentiment analysis is an important research direction of natural language processing. In-depth exploration of online textual emotional information has great social significance social and commercial value for market research, online public opinion discovery and early warning.
Qing Yu, Hui Zhao, Zuohua Wang
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2020 7th International Conference on Behavioural and Social Computing (BESC), 2020
In recent years, various types of network attacks emerge in endlessly, the protection of network security has been paid more and more attention by our society. Network Intrusion Detection System (NIDS)is used to protect computer systems from malicious attacks and intrusions, thus has also become a hot research field.
Jingyi Wang +4 more
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In recent years, various types of network attacks emerge in endlessly, the protection of network security has been paid more and more attention by our society. Network Intrusion Detection System (NIDS)is used to protect computer systems from malicious attacks and intrusions, thus has also become a hot research field.
Jingyi Wang +4 more
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Inter-Person Relation Classification via AttentionBased Bidirectional Gated Recurrent Unit
2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2019Relation classification is a fundamental ingredient in various information extraction systems. To extract personal entity relation from Chinese text, a novel deep neural network architecture is proposed this paper, which employs bidirectional Gated Recurrent Unit (Bi-GRU) by adding attention mechanism to capture important semantic information in a ...
Dandan Zhao +5 more
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Capsule-Based Bidirectional Gated Recurrent Unit Networks for Question Target Classification
2018Question target classification, also known as answer type classification, turns out to be a key step for a high-performance QA system. The task has drawn more and more attention from academia and industry. This work proposes an artificial neural network architecture to classify questions according to their answer types.
Shi Chen, Bing Zheng, Tianyong Hao
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