Research on Autonomous Face Recognition System for Spatial Human-Robotic Interaction Based on Deep Learning

2019 ◽  
pp. 131-141
Author(s):  
Ming Liu ◽  
Na Dong ◽  
Qimeng Tan ◽  
Bixi Yan ◽  
Jingyi Zhao
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Recognition System ◽  
Face Recognition System ◽  
Human Robotic Interaction

An effective face recognition system based on Cloud based IoT with a deep learning model

2021 ◽  
Vol 81 ◽  
pp. 103726
Author(s):  
Deepika Chauhan ◽  
Ashok Kumar ◽  
Pradeep Bedi ◽  
Vijay Anant Athavale ◽  
D. Veeraiah ◽  
...  
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Recognition System ◽  
Learning Model ◽  
Face Recognition System ◽  
Deep Learning Model

A Deep Learning based Approach for Real Time Face Recognition System

2021 ◽  
Author(s):  
Tanusree Das Tithy ◽  
Soarov Chakraborty ◽  
Rabaya Islam ◽  
Abdul Aziz
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Real Time ◽  
Recognition System ◽  
Face Recognition System

scholarly journals Transition from Holistic to Deep learning Face Recognition Methods

2019 ◽  
Vol 8 (4) ◽  
pp. 3111-3116
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Healthcare Access ◽  
Hybrid Approach ◽  
Recognition System ◽  
Learning Approach ◽  
Holistic Learning ◽  
Face Representation ◽  
Face Recognition System ◽  
The Face

Face recognition, the fastest growing biometric technology of computer vision, made a breakthrough in the field of security, healthcare, access control and marketing etc. This technology helps in automatically discern and identify the faces for authentication by comparing available digital image of faces. Various algorithms have been developed for enhancing the performance of face recognition system. The face authentication system entails three major steps, face detection, feature extraction and face recognition. This paper provides some of the major milestones of face representation for recognition like holistic learning approach, feature based approach, hybrid approach and deep learning approach. The various techniques under these categories are reviewed. Finally, implemented face recognition using convolution neural network (CNN). In this method, the image is captured through webcam for the dataset preparation. The detection is carried out by CNN cascade, followed by face landmark and face embedding by FaceNet CNN. Recognition of face is performed after training the network. Implemented faces recognition successfully and accurately for smaller dataset.

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