Design of internet of things online oral English teaching platform based on long-term and short-term memory network

2021 ◽  
Vol 31 (1) ◽  
pp. 104
Author(s):  
Shunmeng Chen
Keyword(s):  
Internet Of Things ◽  
Short Term Memory ◽  
Short Term ◽  
Term Memory ◽  
English Teaching ◽  
Teaching Platform ◽  
Memory Network

Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network

2019 ◽  
Vol 239 ◽  
pp. 181-191 ◽  
Author(s):  
Shuang Han ◽  
Yan-hui Qiao ◽  
Jie Yan ◽  
Yong-qian Liu ◽  
Li Li ◽  
...  
Keyword(s):  
Power Generation ◽  
Short Term Memory ◽  
Copula Function ◽  
Short Term ◽  
Term Memory ◽  
Photovoltaic Power ◽  
Memory Network ◽  
Long Short Term Memory

scholarly journals Research on Volleyball Video Intelligent Description Technology Combining the Long-Term and Short-Term Memory Network and Attention Mechanism

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuhua Gao ◽  
Yong Mo ◽  
Heng Zhang ◽  
Ruiyin Huang ◽  
Zilong Chen
Keyword(s):  
Language Processing ◽  
Visual Information ◽  
High Speed ◽  
Short Term Memory ◽  
Attention Mechanism ◽  
Short Term ◽  
Term Memory ◽  
Video Description ◽  
Memory Network

With the development of computer technology, video description, which combines the key technologies in the field of natural language processing and computer vision, has attracted more and more researchers’ attention. Among them, how to objectively and efficiently describe high-speed and detailed sports videos is the key to the development of the video description field. In view of the problems of sentence errors and loss of visual information in the generation of the video description text due to the lack of language learning information in the existing video description methods, a multihead model combining the long-term and short-term memory network and attention mechanism is proposed for the intelligent description of the volleyball video. Through the introduction of the attention mechanism, the model pays much attention to the significant areas in the video when generating sentences. Through the comparative experiment with different models, the results show that the model with the attention mechanism can effectively solve the loss of visual information. Compared with the LSTM and base model, the multihead model proposed in this paper, which combines the long-term and short-term memory network and attention mechanism, has higher scores in all evaluation indexes and significantly improved the quality of the intelligent text description of the volleyball video.

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