Deep Learning-Based Facial Recognition on Hybrid Architecture for Financial Services

Almost all financial services (especially digital payments) in China are affected by new innovations and technologies. New technologies such as blockchain, artificial intelligence, machine learning, deep learning, and data analytics have immensely influenced all most all aspects of financial services such as deposits, transactions, billings, remittances, credits (B2B and P2P), underwriting, insurance, and so on. Fintech companies are enabling larger financial inclusion, changing in lifestyle and expenditure behavior, better and fast financial services, and lots more. This chapter covers the development, opportunities, and challenges of financial sectors because of new technologies in China. This chapter throws the light on opportunities that emerged because of the large population of 1.4 billion people, high penetration, and access to the latest and affordable technology, affordable cost of smartphones, and government policies and regulations. Lastly, this chapter portrays the untapped potentials of Fintech in China.

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Design of Intelligent classroom facial recognition based on Deep Learning

Journal of Physics Conference Series ◽

10.1088/1742-6596/1168/2/022043 ◽

2019 ◽

Vol 1168 ◽

pp. 022043 ◽

Cited By ~ 2

Author(s):

Jielong Tang ◽

Xiaotian Zhou ◽

Jiawei Zheng

Keyword(s):

Deep Learning ◽

Facial Recognition ◽

Intelligent Classroom

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Design of facial recognition system implemented in an unmanned aerial vehicle for citizen security in Latin America

ITM Web of Conferences ◽

10.1051/itmconf/20192704002 ◽

2019 ◽

Vol 27 ◽

pp. 04002

Author(s):

Diego Herrera ◽

Hiroki Imamura

Keyword(s):

Neural Network ◽

Latin America ◽

Deep Learning ◽

Mobile Devices ◽

Unmanned Aerial Vehicle ◽

Facial Recognition ◽

Recognition System ◽

Criminal Records ◽

Aerial Vehicle ◽

Facial Recognition System

In the new technological era, facial recognition has become a central issue for a great number of engineers. Currently, there are a great number of techniques for facial recognition, but in this research, we focus on the use of deep learning. The problems with current facial recognition convection systems are that they are developed in non-mobile devices. This research intends to develop a Facial Recognition System implemented in an unmanned aerial vehicle of the quadcopter type. While it is true, there are quadcopters capable of detecting faces and/or shapes and following them, but most are for fun and entertainment. This research focuses on the facial recognition of people with criminal records, for which a neural network is trained. The Caffe framework is used for the training of a convolutional neural network. The system is developed on the NVIDIA Jetson TX2 motherboard. The design and construction of the quadcopter are done from scratch because we need the UAV for adapt to our requirements. This research aims to reduce violence and crime in Latin America.

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