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Application Research on Satisfaction Evaluation of Clothing Advertising based on Micro Expression Recognition Technology


Affiliations
1 Textile Engineering, Hunan Institute of Engineering,Xiangtan，411104, China
2 College of computer and communication, Hunan institute of engineering, Xiangtan，411104, China
 

Questionnaire is one of the most important means to collect data and make information decision. In this paper, the micro expression recognition technology of artificial intelligence is applied in the field of print advertising satisfaction collection and information decision-making. Starting with the analysis of micro expression, a new concept of satisfaction factor of print advertising is proposed and then various optimization functions in neural network are analyzed and discussed. In the following part, the Adabound optimization function is applied to the network model in the example of clothing print advertisement and the convergence s peed of the loss function is accelerated in order to improve the detection accuracy of the model. Experimental result shows the satisfaction of the viewers to the clothing print advertisements, allowing researchers to judge their purchase desire at the same time

Keywords

Clothing print advertising; micro expression recognition; satisfaction; Adabound.
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  • Application Research on Satisfaction Evaluation of Clothing Advertising based on Micro Expression Recognition Technology

Abstract Views: 133  |  PDF Views: 1

Authors

Wang Kai
Textile Engineering, Hunan Institute of Engineering,Xiangtan，411104, China
He Hong
College of computer and communication, Hunan institute of engineering, Xiangtan，411104, China

Abstract


Questionnaire is one of the most important means to collect data and make information decision. In this paper, the micro expression recognition technology of artificial intelligence is applied in the field of print advertising satisfaction collection and information decision-making. Starting with the analysis of micro expression, a new concept of satisfaction factor of print advertising is proposed and then various optimization functions in neural network are analyzed and discussed. In the following part, the Adabound optimization function is applied to the network model in the example of clothing print advertisement and the convergence s peed of the loss function is accelerated in order to improve the detection accuracy of the model. Experimental result shows the satisfaction of the viewers to the clothing print advertisements, allowing researchers to judge their purchase desire at the same time

Keywords


Clothing print advertising; micro expression recognition; satisfaction; Adabound.

References