Burning state recognition of rotary kiln using ELMs with heterogeneous features

2013 ◽  
Vol 102 ◽  
pp. 144-153 ◽  
Author(s):  
Weitao Li ◽  
Dianhui Wang ◽  
Tianyou Chai
Keyword(s):  
Rotary Kiln ◽  
State Recognition ◽  
Heterogeneous Features

A solar heated rotary kiln for the detoxification of hazardous wastes

1999 ◽  
Vol 09 (PR3) ◽  
pp. Pr3-307-Pr3-312 ◽  
Author(s):  
B. Pohlmann ◽  
K.-H. Funken ◽  
R. Dominik
Keyword(s):  
Rotary Kiln ◽  
Hazardous Wastes

Recognition of classroom student state features based on deep learning algorithms and machine learning

2020 ◽  
pp. 1-12
Author(s):  
Hu Jingchao ◽  
Haiying Zhang
Keyword(s):  
Deep Learning ◽  
Feature Recognition ◽  
Subjective Evaluation ◽  
Recognition Algorithm ◽  
Video Data ◽  
State Recognition ◽  
Detection Model ◽  
State Classification ◽  
Intelligent Models ◽  
Model Recognition

The difficulty in class student state recognition is how to make feature judgments based on student facial expressions and movement state. At present, some intelligent models are not accurate in class student state recognition. In order to improve the model recognition effect, this study builds a two-level state detection framework based on deep learning and HMM feature recognition algorithm, and expands it as a multi-level detection model through a reasonable state classification method. In addition, this study selects continuous HMM or deep learning to reflect the dynamic generation characteristics of fatigue, and designs random human fatigue recognition experiments to complete the collection and preprocessing of EEG data, facial video data, and subjective evaluation data of classroom students. In addition to this, this study discretizes the feature indicators and builds a student state recognition model. Finally, the performance of the algorithm proposed in this paper is analyzed through experiments. The research results show that the algorithm proposed in this paper has certain advantages over the traditional algorithm in the recognition of classroom student state features.

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