Results 11 to 20 of about 13,592 (226)
Peramalan Data Indeks Harga Konsumen Berbasis Time Series Multivariate Menggunakan Deep Learning
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2021 Multivariate Time Series based forecasting is a type of forecasting that has more than one criterion changes from time to time that it can forecast based on historical patterns of data sequences.
Soffa Zahara, Sugianto
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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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Learning Fashion Compatibility with Bidirectional LSTMs [PDF]
Proceedings of the 25th ACM international conference on Multimedia, 2017 ACM MM ...
Xintong Han +3 more
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Machine Learning with Applications, 2022 Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others.
Ari Yair Barrera-Animas +5 more
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Agriculture, 2022 Cattle behaviour is a significant indicator of cattle welfare. With the advancements in electronic equipment, monitoring and classifying multiple cattle behaviour patterns is becoming increasingly important in precision livestock management.
Yiqi Wu +5 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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Hybrid speech recognition with Deep Bidirectional LSTM [PDF]
2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 2013 Deep Bidirectional LSTM (DBLSTM) recurrent neural networks have recently been shown to give state-of-the-art performance on the TIMIT speech database. However, the results in that work relied on recurrent-neural-network-specific objective functions, which are difficult to integrate with existing large vocabulary speech recognition systems.
Alex Graves +2 more
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PLoS ONE, 2021 A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace ...
Fu-Shun Hsu +17 more
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Deep learning-based method for sentiment analysis for patients’ drug reviews [PDF]
PeerJ Computer ScienceThis article explores the application of deep learning techniques for sentiment analysis of patients’ drug reviews. The main focus is to evaluate the effectiveness of bidirectional long-short-term memory (LSTM) and a hybrid model (bidirectional LSTM-CNN)
Sena Al-Hadhrami +4 more
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