Results 31 to 40 of about 15,297,754 (301)

Event Trigger Word Extraction Based on Convolutional Bidirectional Long Short Term Memory Network [PDF]

Jisuanji gongcheng, 2019
The traditional event trigger word extraction methods over rely on Natural Language Processing(NLP) tools in the feature extraction process,which is easy to cause error accumulation.To solve this problem,a new event trigger extraction based on ...
CHEN Bin,ZHOU Yong,LIU Bing
doaj   +1 more source

Long short-term memory networks in memristor crossbar arrays [PDF]

Nature Machine Intelligence, 2019
Recent breakthroughs in recurrent deep neural networks with long short-term memory (LSTM) units have led to major advances in artificial intelligence. However, state-of-the-art LSTM models with significantly increased complexity and a large number of parameters have a bottleneck in computing power resulting from both limited memory capacity and limited
Can Li 0024, Zhongrui Wang, Mingyi Rao, Daniel Belkin, Wenhao Song, Hao Jiang 0017, Peng Yan, Yunning Li, Peng Lin, Miao Hu 0002, Ning Ge 0001, John Paul Strachan, Mark Barnell, Qing Wu 0002, R. Stanley Williams, J. Joshua Yang, Qiangfei Xia   +16 more
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A Novel Network Architecture of Decision-Making for Self-Driving Vehicles Based on Long Short-Term Memory and Grasshopper Optimization Algorithm

IEEE Access, 2020
Long short-term memory network is one of the most important network architectures of decision-making for self-driving vehicles. Nevertheless, the decision-making accuracy of long short-term memory network is limited, the information of the surrounding ...
Yunxia Shi, Ying Li, Jiahao Fan, Tan Wang, Taiqiao Yin   +4 more
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Detection of Myocardial Infarction Using Hybrid Models of Convolutional Neural Network and Recurrent Neural Network

BioMedInformatics, 2023
Myocardial Infarction (MI) is the death of the heart muscle caused by lack of oxygenated blood flow to the heart muscle. It has been the main cause of death worldwide.
Sumayyah Hasbullah, Mohd Soperi Mohd Zahid, Satria Mandala   +2 more
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Mitigating Catastrophic Forgetting in Long Short-Term Memory Networks

CoRR, 2023
Continual learning on sequential data is critical for many machine learning (ML) deployments. Unfortunately, LSTM networks, which are commonly used to learn on sequential data, suffer from catastrophic forgetting and are limited in their ability to learn multiple tasks continually.
Ketaki Joshi, Raghavendra Pradyumna Pothukuchi, Andre Wibisono, Abhishek Bhattacharjee   +3 more
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Linking working memory and long-term memory: A computational model of the learning of new words [PDF]

, 2007
The nonword repetition (NWR) test has been shown to be a good predictor of children’s vocabulary size. NWR performance has been explained using phonological working memory, which is seen as a critical component in the learning of new words.
Julian M. Pine, Pine, J M, Fernand Gobet, Gary Jones, Jones, G, Gobet, F   +5 more
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CMIP and ATP2C2 Modulate Phonological Short-Term Memory in Language Impairment [PDF]

, 2009
Specific language impairment (SLI) is a common developmental disorder characterized by difficulties in language acquisition despite otherwise normal development and in the absence of any obvious explanatory factors.
Dworzynski, K., Helms, P., Dorothy V.M. Bishop, Helms, Peter J., Newbury, D., Hennessy, E, Addis, Laura, Andrea Everitt, Pickles, A, Seckl, J, Addis, L., Buckingham, Lyn-Louise, Helms, P. J., Anne O'Hare, Bishop, Dorothy V.M., Slonims, V., Emily Simonoff, Silvia Paracchini, Andrew Pickles, Slonims, Vicky, O'Hare, A, Simkin, Z, Simonoff, Emily, Duncan Shaw, Winchester, L, Pickles, A., Kindley, AD, Everitt, A., Vicky Slonims, Seckl, J. R., Bishop, DV, Clark, Ann, Gina Conti-Ramsden, Cohen, W., Buckingham, L., Conti-Ramsden, G., Hilary Cowie, Monaco, Anthony P., Seckl, J., Baird, Gillian, Cowie, Hilary, Newbury, D F, Hennessy, E., Newbury, D. F., Goodyer, Ian M., Baird, G., Katharina Dworzynski, Laura Winchester, Cohen, Wendy, Laura Addis, Buckingham, LL, Kindley, A. D., Hennessy, Elizabeth, Nasir, J., Helms, PJ, Conti-Ramsden, Gina, Bishop, D., Fisher, Simon, Paracchini, S, Goodyer, IM, Dworzynski, KD, Everitt, Andrea, Pickles, Andrew, Clark, A, Jamal Nasir, Jiannis Ragoussis, Shaw, D., Siminoff, E, Newbury, DF, Bolton, Patrick F., Lyn-Louise Buckingham, Paracchini, S., Dianne F. Newbury, Simkin, Zoe, Fisher, S. E., Anthony P. Monaco, Simkin, Z., Goodyer, I. M., Goodyer, I., Buckingham, Lyn Louise, Zoe Simkin, Miller, Laura L., O'Hare, A., Ian M. Goodyer, Ragoussis, J., Clark, A., Miller, L. L., Simonoff, Emily; id_orcid, Ragoussis, Jiannis, Wendy Cohen, Nasir, J, Ann Clark, Miller, LL, Dworzynski, Katharina, Seckl, JR, Monaco, AP, Ragoussis, Ioannis, Seckl, Jonathon R., Simon E. Fisher, Patrick F. Bolton, O'Hare, Anne, Shaw, D, Addis, L, Bishop, D. V. M., Ragoussis, J, Everitt, A, Watson, J, Peter J. Helms, Cowie, H., Cohen, W, Miller, L., Monaco, A., Paracchini, Silvia, Watson, J., Bolton, PF, Newbury, Dianne, Bolton, P. F., Buckingham, L. L., Shaw, Darren, Monaco, Anthony, Bishop, Dorothy V. M., Miller, Laura L, Jocelynne Watson, Dworzynski, K, Kindley, A. David, Kindley, A., A. David Kindley, Laura L. Miller, Baird, G, Fisher, S., Bolton, P., Fisher, SE, Conti-Ramsden, G, Cowie, H, Monaco, A. P., Slonims, V, Nasir, Jamal, Winchester, L., Bishop, DVM, Watson, Jocelynne, Newbury, Dianne F., Simonoff, E, Winchester, Laura, Jonathon R. Seckl, Gillian Baird, Simonoff, E., Fisher, Simon E., Elizabeth Hennessy, Bishop, Dorothy, Shaw, Duncan   +149 more
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Website Visitors Forecasting using Recurrent Neural Network Method

JITeCS (Journal of Information Technology and Computer Science), 2021
. The number of visitors and content accessed by users on a site shows the performance of the site. Therefore, forecasting needs to be done to find out how many users a website will come.
Putu Bagus Arya, Wayan Firdaus Mahmudy, Achmad Basuki   +2 more
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Short-term memory as a working memory control process [PDF]

, 2013
Aben et al. (2012) take issue with the unthoughtful use of the terms “working memory” (WM) and “short-term memory” (STM) in the cognitive and neuroscientific literature.
Eddy J Davelaar, Eddy J. Davelaar, Davelaar, Eddy J.   +2 more
core   +1 more source

Short‐term natural gas consumption prediction based on wavelet transform and bidirectional long short‐term memory optimized by Bayesian network

Energy Science & Engineering, 2022
In the energy structure, natural gas is an important clean energy, and its consumption forecast is of great significance for energy policy formulation, pipeline network planning design, and peak shaving capacity determination. In the field of forecasting,
Zhaoyang Li, Liang Liu, Weibiao Qiao
doaj   +1 more source