A visual discomfort recognition model based on the fusion of multisource information

2021 ◽  
Author(s):  
Yunyang Shi ◽  
Yan Tu ◽  
Lili Wang ◽  
Yin Zhang ◽  
Xin Gao
Keyword(s):  
Visual Discomfort ◽  
Recognition Model ◽  
Model Based

scholarly journals DeepWTPCA-L1: A New Deep Face Recognition Model Based on WTPCA-L1 Norm Features

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 65091-65100
Author(s):  
Ayyad Maafiri ◽  
Omar Elharrouss ◽  
Saad Rfifi ◽  
Somaya Ali Al-Maadeed ◽  
Khalid Chougdali
Keyword(s):  
Face Recognition ◽  
L1 Norm ◽  
Recognition Model ◽  
Model Based

Attribute Recognition Model Based on Entropy Weight and Its Application to Evaluation of Groundwater Quality

2010 ◽  
Vol 29-32 ◽  
pp. 2698-2702
Author(s):  
Xian Qi Zhang ◽  
Wen Hong Feng ◽  
Nan Nan Li
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Information Entropy ◽  
Simple Calculation ◽  
Weight Coefficient ◽  
Entropy Theory ◽  
Entropy Weight ◽  
Recognition Model ◽  
Model Based ◽  
Attribute Recognition

It is necessary to take into account synthetically attribute of every index because of independence and incompatibility resulted from single index evaluating outcomes. Through the information entropy theory and attribute recognition model being combined together, attribute recognition model based on entropy weight is constructed and applied to evaluating groundwater quality by a new method, weight coefficient by the law of entropy value is exercised so that it is more objective. The outcome from concrete application indicates that it is suitable to evaluate water quality with reasonable conclusion and simple calculation.

Simulation of English text recognition model based on ant colony algorithm and genetic algorithm

2021 ◽  
pp. 1-12
Author(s):  
Fei Long
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Text Recognition ◽  
English Text ◽  
Recognition Model ◽  
Central Node ◽  
Model Based ◽  
Characteristic Points

The difficulty of English text recognition lies in fuzzy image text classification and part-of-speech classification. Traditional models have a high error rate in English text recognition. In order to improve the effect of English text recognition, guided by machine learning ideas, this paper combines ant colony algorithm and genetic algorithm to construct an English text recognition model based on machine learning. Moreover, based on the characteristics of ant colony intelligent algorithm optimization, a method of using ant colony algorithm to solve the central node is proposed. In addition, this paper uses the ant colony algorithm to obtain the characteristic points in the study area and determine a reasonable number, and then combine the uniform grid to select some non-characteristic points as the central node of the core function, and finally use the central node with a reasonable distribution for modeling. Finally, this paper designs experiments to verify the performance of the model constructed in this paper and combines mathematical statistics to visually display the experimental results using tables and graphs. The research results show that the performance of the model constructed in this paper is good.

GaitSlice: A gait recognition model based on spatio-temporal slice features

2021 ◽  
pp. 108453
Author(s):  
Huakang Li ◽  
Yidan Qiu ◽  
Huimin Zhao ◽  
Jin Zhan ◽  
Rongjun Chen ◽  
...  
Keyword(s):  
Gait Recognition ◽  
Recognition Model ◽  
Model Based ◽  
Spatio Temporal
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