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

2021 ◽  
pp. 51-70
Author(s):  
Oscar Granados ◽  
Olmer Garcia-Bedoya
Keyword(s):  
Deep Learning ◽  
Financial Services ◽  
Facial Recognition ◽  
Hybrid Architecture

FinTech Adoption in China

2021 ◽  
pp. 166-173
Author(s):  
Gagan Kukreja
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Financial Services ◽  
New Technologies ◽  
Large Population ◽  
Financial Inclusion ◽  
High Penetration ◽  
Digital Payments ◽  
Almost All

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.

scholarly journals Design of Intelligent classroom facial recognition based on Deep Learning

2019 ◽  
Vol 1168 ◽  
pp. 022043 ◽  
Author(s):  
Jielong Tang ◽  
Xiaotian Zhou ◽  
Jiawei Zheng
Keyword(s):  
Deep Learning ◽  
Facial Recognition ◽  
Intelligent Classroom

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

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.

scholarly journals Automated facial recognition for wildlife that lack unique markings: A deep learning approach for brown bears

2020 ◽  
Vol 10 (23) ◽  
pp. 12883-12892
Author(s):  
Melanie Clapham ◽  
Ed Miller ◽  
Mary Nguyen ◽  
Chris T. Darimont
Keyword(s):  
Deep Learning ◽  
Facial Recognition ◽  
Learning Approach ◽  
Brown Bears
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