Results 21 to 30 of about 16,939 (236)

Learning Fashion Compatibility with Bidirectional LSTMs [PDF]

Proceedings of the 25th ACM international conference on Multimedia, 2017
ACM MM ...
Xintong Han, Zuxuan Wu, Yu-Gang Jiang 0001, Larry S. Davis   +3 more
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Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting

, 2023
Accurate forecasting of rainfall is extremely important due to its complex nature and enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant concentration levels.
Yaseen, Zaher Mundher, Malik, Anurag, Ali, Mumtaz, Rai, Priya, Karbasi, Masoud, Jamei, Mehdi   +5 more
core   +1 more source

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, Navdeep Jaitly, Abdel-rahman Mohamed   +2 more
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Near real-time wind speed forecast model with bidirectional LSTM networks

, 2023
Wind is an important source of renewable energy, often used to provide clean electricity to remote areas. For optimal extraction of this energy source, there is a need for an accurate and robust wind speed forecasting.
Deo, Ravinesh C., Soar, Jeffrey, Joseph, Lionel P., Prasad, Ramendra, Salcedo-Sanz, Sancho, Raj, Nawin   +5 more
core   +1 more source

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1.

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, Shang-Ran Huang, Chien-Wen Huang, Chao-Jung Huang, Yuan-Ren Cheng, Chun-Chieh Chen, Jack Hsiao, Chung-Wei Chen, Li-Chin Chen, Yen-Chun Lai, Bi-Fang Hsu, Nian-Jhen Lin, Wan-Ling Tsai, Yi-Lin Wu, Tzu-Ling Tseng, Ching-Ting Tseng, Yi-Tsun Chen, Feipei Lai   +17 more
doaj   +1 more source

Deep learning-based method for sentiment analysis for patients’ drug reviews [PDF]

PeerJ Computer Science
This 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, Tamas Vinko, Tawfik Al-Hadhrami, Faisal Saeed, Sultan Noman Qasem   +4 more
doaj   +2 more sources

Seizure Prediction Using Bidirectional LSTM [PDF]

, 2019
Approximately, 50 million people in the world are affected by epilepsy. For patients, the anti-epileptic drugs are not always useful and these drugs may have undesired side effects on a patient's health. If the seizure is predicted the patients will have enough time to take preventive measures. The purpose of this work is to investigate the application
Hazrat Ali, Feroz Karim, Junaid Javed Qureshi, Adnan Omer Abuassba, Mohammad Farhad Bulbul   +4 more
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Deep Bidirectional LSTM Network Learning-Aided OFDMA Downlink and SC-FDMA Uplink

, 2021
In this paper, deep learning (DL)-aided signal detection is proposed for the orthogonal frequency division multiple access (OFDMA) in the downlink and for the single carrier frequency division multiple access (SC-FDMA) in the uplink. A deep bidirectional
Saha, Ritu, Awal, Md Abdul, Mohammad Ismat Kadir, Kadir, Rafiul, Ritu Saha, Rafiul Kadir, Md. Abdul Awal, Kadir, Mohammad Ismat   +7 more
core   +1 more source

Sentiment analysis from textual data using multiple channels deep learning models

Journal of Electrical Systems and Information Technology, 2023
Text sentiment analysis has been of great importance over the last few years. It is being widely used to determine a person’s feelings, opinions and emotions on any topic or for someone.
Adepu Rajesh, Tryambak Hiwarkar
doaj   +1 more source

Framewise phoneme classification with bidirectional LSTM networks [PDF]

Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., 2006
In this paper, we apply bidirectional training to a long short term memory (LSTM) network for the first time. We also present a modified, full gradient version of the LSTM learning algorithm. We discuss the significance of framewise phoneme classification to continuous speech recognition, and the validity of using bidirectional networks for online ...
Alex Graves, Jürgen Schmidhuber
openaire   +1 more source