A Power-Efficient Security Device Leveraging Deep Learning (DL)-Inspired Facial Recognition

2020 ◽  
pp. 589-597
Author(s):  
R. S. Saundharya Thejaswini ◽  
S. Rajaraajeswari ◽  
Pethuru Raj
Keyword(s):  
Deep Learning ◽  
Facial Recognition ◽  
Power Efficient ◽  
Security Device

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 A Cost-Effective Person-Following System for Assistive Unmanned Vehicles with Deep Learning at the Edge

Machines ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 49
Author(s):  
Anna Boschi ◽  
Francesco Salvetti ◽  
Vittorio Mazzia ◽  
Marcello Chiaberge
Keyword(s):  
Deep Learning ◽  
Cost Effective ◽  
Vital Statistics ◽  
Unmanned Vehicles ◽  
Optimization Techniques ◽  
World Population ◽  
Service Robotics ◽  
Power Efficient ◽  
Person Following ◽  
The World

The vital statistics of the last century highlight a sharp increment of the average age of the world population with a consequent growth of the number of older people. Service robotics applications have the potentiality to provide systems and tools to support the autonomous and self-sufficient older adults in their houses in everyday life, thereby avoiding the task of monitoring them with third parties. In this context, we propose a cost-effective modular solution to detect and follow a person in an indoor, domestic environment. We exploited the latest advancements in deep learning optimization techniques, and we compared different neural network accelerators to provide a robust and flexible person-following system at the edge. Our proposed cost-effective and power-efficient solution is fully-integrable with pre-existing navigation stacks and creates the foundations for the development of fully-autonomous and self-contained service robotics applications.

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

Application of Deep Learning in Facial Recognition

2021 ◽  
pp. 195-207
Author(s):  
Jimit Gandhi ◽  
Aditya Jeswani ◽  
Fenil Doshi ◽  
Parth Doshi ◽  
Ramchandra S. Mangrulkar
Keyword(s):  
Deep Learning ◽  
Facial Recognition
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