Recurrent neural network application to image filtering: 2-D Kalman filtering approach

1991 ◽  
Author(s):  
Roman W. Swiniarski ◽  
Andrzej Dzielinski ◽  
Slawomir Skoneczny ◽  
Michael P. Butler
Keyword(s):  
Neural Network ◽  
Kalman Filtering ◽  
Recurrent Neural Network ◽  
Image Filtering ◽  
Network Application ◽  
Filtering Approach

DeepResGRU: Residual gated recurrent neural network-augmented Kalman filtering for speech enhancement and recognition

2021 ◽  
pp. 107914
Author(s):  
Nasir Saleem ◽  
Jiechao Gao ◽  
Muhammad Irfan Khattak ◽  
Hafiz Tayyab Rauf ◽  
Seifedine Kadry ◽  
...  
Keyword(s):  
Neural Network ◽  
Speech Enhancement ◽  
Kalman Filtering ◽  
Recurrent Neural Network

Research on behavior recognition based on feature fusion of automatic coder and recurrent neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8927-8935
Author(s):  
Bing Zheng ◽  
Dawei Yun ◽  
Yan Liang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Video Data ◽  
Support Vector ◽  
Behavior Recognition ◽  
Learning Methods ◽  
The Impact ◽  
Internet Of Things Technology

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition.

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