Results 11 to 20 of about 16,939 (236)
Synthesizing Mesh Deformation Sequences With Bidirectional LSTM [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2022 Synthesizing realistic 3D mesh deformation sequences is a challenging but important task in computer animation. To achieve this, researchers have long been focusing on shape analysis to develop new interpolation and extrapolation techniques. However, such techniques have limited learning capabilities and therefore often produce unrealistic deformation.
Yi-Ling Qiao +3 more
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Research on Nonintrusive Load Decomposition of Enterprises Based on Bidirectional LSTM [PDF]
E3S Web of Conferences, 2021 To detect the operating condition of equipment and understand the environmental management situation of enterprises in real-time, this paper studies the non-intrusive load decomposition of enterprises based on bidirectional LSTM.
Yu Xiangqian +4 more
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Advanced Network Traffic Prediction Using Deep Learning Techniques: A Comparative Study of SVR, LSTM, GRU, and Bidirectional LSTM Models [PDF]
ITM Web of ConferencesAccurate prediction of network traffic patterns is essential for optimizing network resource allocation, managing congestion, and strengthening cybersecurity. This study examines the effectiveness of four machine learning models—Support Vector Regression
Wang Yuxin
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Bidirectional LSTM-CRF for Clinical Concept Extraction [PDF]
CoRR, 2016 This paper "Bidirectional LSTM-CRF for Clinical Concept Extraction" is accepted for short paper presentation at Clinical Natural Language Processing Workshop at COLING 2016 Osaka, Japan.
Raghavendra Chalapathy +2 more
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A Stock Prediction Method Based on Heterogeneous Bidirectional LSTM
Applied SciencesLSTM (long short-term memory) networks have been proven effective in processing stock data. However, the stability of LSTM is poor, it is greatly affected by data fluctuations, and it is weak in capturing long-term dependencies in sequential data. BiLSTM
Shuai Sang, Lu Li
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Vehicle Destination Prediction Using Bidirectional LSTM with Attention Mechanism. [PDF]
Sensors (Basel), 2021 Satellite navigation has become ubiquitous to plan and track travelling. Having access to a vehicle’s position enables the prediction of its destination.
Casabianca P +3 more
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Image captioning using bidirectional LSTM neural network
Discover Artificial IntelligenceAutomatic image captioning is a crucial task in image processing and machine vision, where images are segmented into regions, and captions are assigned based on shared attributes.
Farnaz Hoseini, Anaram Yaghoobi Notash
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Disfluency Detection Using a Bidirectional LSTM [PDF]
Interspeech 2016, 2016 We introduce a new approach for disfluency detection using a Bidirectional Long-Short Term Memory neural network (BLSTM). In addition to the word sequence, the model takes as input pattern match features that were developed to reduce sensitivity to vocabulary size in training, which lead to improved performance over the word sequence alone.
Vicky Zayats +2 more
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Head-Lexicalized Bidirectional Tree LSTMs [PDF]
Transactions of the Association for Computational Linguistics, 2017 Sequential LSTMs have 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
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Image Captioning with Deep Bidirectional LSTMs [PDF]
Proceedings of the 24th ACM international conference on Multimedia, 2016 This work presents an end-to-end trainable deep bidirectional LSTM (Long-Short Term Memory) model for image captioning. Our model builds on a deep convolutional neural network (CNN) and two separate LSTM networks. It is capable of learning long term visual-language interactions by making use of history and future context information at high level ...
Cheng Wang 0002 +3 more
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