Video Face Recognition of Virtual Currency Trading System Based on Deep Learning Algorithms

Wei, Jun

doi:10.1109/access.2021.3060458

Cited by 9 publications

(6 citation statements)

References 29 publications

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“…In today's era, in the face of the great adjustment and change of the world pattern, the frequent intermingling of various ideologies and cultures, and the rise of China, many developed countries are anxious in the international arena, and in the international arena, the western hostile forces are using all available forms to constantly infiltrate and invade China culturally and develop various cultural communication channels to spread their “free thinking” and “hedonism.” They are trying to assimilate China ideologically and culturally by developing various cultural channels of communication and spreading their “free thinking” and “hedonism,” and by propagating their ideology. In China, with the rise of the market economy and the infiltration of western culture, the development of the Chinese cultural market has lagged and is relatively imperfect [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Contemporary Value Assessment of Marxist Ideology under the Context of Deep Learning

Jian

2022

Computational and Mathematical Methods in Medicine

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As a conceptual superstructure, ideology plays a very important role in national security, social stability, and healthy economic development. As a result, ideological work is critical to the Party’s success, and the current focus of ideological work is to increase ideological risk prevention. The focus of ideological risk avoidance is gradually shifting to cyberspace as the Internet becomes the primary arena and forum for information interchange, value dissemination, and ideological exchanges. Deep learning, as a data processing technology, is characterized by deep data analysis and full generalization and can have an impact on ideological security work: on the one hand, it helps work subjects evaluate and count the process and effect of work in order to grasp the trend of public opinion; on the other hand, it helps work subjects understand and reflect on the inner logic and contemporary value of Marxist theory through diversified work platforms and diverse work methods and promotes work subjects’ understanding of Marxist theory. On the other hand, through diversified working platforms and various working methods, we help the working targets to understand and reflect on the inner logic and contemporary values of Marxist theory and promote their true identification with socialist core values. Based on the impact of deep learning on work subjects and work objects, this paper proposes that Marxian ideological security workers can use it to effectively achieve good communication and contemporary value assessment among different work subjects, set specific indicators according to the division of labour, adopt different working methods according to the groups to which the learning bjects belong, and establish a long-term evaluation mechanism in the process.

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Section: Introductionmentioning

confidence: 99%

Contemporary Value Assessment of Marxist Ideology under the Context of Deep Learning

Jian

2022

Computational and Mathematical Methods in Medicine

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“…All the results in Figs. [8][9][10][11] shown that our model has a good performance in dealing with information loss.…”

Section: Model Performance Of Ir 3 C With a Triplet Lossmentioning

confidence: 78%

“…Computational intelligence in face recognition based on visible images has been rapidly developed and widely used in many practical scenarios, such as security [1][2][3][4][5][6][7][8][9], finance [10][11][12][13][14][15][16][17][18][19], and health care service [20][21][22][23][24][25][26][27][28][29]. However, limited by lighting conditions [30][31][32][33], facial expression [34,35], pose [36,37], occlusion [38,39], and other confounding factors [40], some valuable information are easily to be lost.…”

Section: Introductionmentioning

confidence: 99%

Broad Learning System for Tackling Emerging Challenges in Face Recognition

Zhang¹,

Wang²

2023

Computer Modeling in Engineering &Amp; Sciences

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Face recognition has been rapidly developed and widely used. However, there is still considerable uncertainty in the computational intelligence based on human-centric visual understanding. Emerging challenges for face recognition are resulted from information loss. This study aims to tackle these challenges with a broad learning system (BLS). We integrated two models, IR 3 C with BLS and IR 3 C with a triplet loss, to control the learning process. In our experiments, we used different strategies to generate more challenging datasets and analyzed the competitiveness, sensitivity, and practicability of the proposed two models. In the model of IR 3 C with BLS, the recognition rates for the four challenging strategies are all 100%. In the model of IR 3 C with a triplet loss, the recognition rates are 94.61%, 94.61%, 96.95%, 96.23%, respectively. The experiment results indicate that the proposed two models can achieve a good performance in tackling the considered information loss challenges from face recognition.

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“…Iris recognition requires the active cooperation of the identified person, and there is a potential damage to the human eye. In view of the above problems, to build a relatively safe and feasible airport channel management system, it must meet the requirements of centralized monitoring and remote control, large system information capacity, complete prevention function, simple transmission mode, stable system operation, simple operation and maintenance [5] .…”

Section: Introductionmentioning

confidence: 99%