scholarly journals Recent Advances in Deep Learning Techniques for Face Recognition

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Md. Tahmid Hasan Fuad ◽  
Awal Ahmed Fime ◽  
Delowar Sikder ◽  
Md. Akil Raihan Iftee ◽  
Jakaria Rabbi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Recent Advances ◽  
Learning Techniques

Real Time Gender and Age Prediction using Deep Learning Techniques

2020 ◽  
Vol 9 (6) ◽  
pp. 797-801
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Real Time ◽  
Vital Role ◽  
Learning Techniques ◽  
Gender And Age ◽  
The Face ◽  
And Gender ◽  
Gender Detection ◽  
Age Prediction

Face recognition plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.

scholarly journals Smart Attendance Management System using Face Recognition

2021 ◽  
Vol 9 (VI) ◽  
pp. 3007-3011
Author(s):  
Nitin .
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Model Building ◽  
Facial Feature ◽  
Human Interactions ◽  
Learning Techniques ◽  
The Face ◽  
Face Detection And Recognition ◽  
Daily Attendance ◽  
The Given

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. In human interactions, the face is the most important factor as it contains important information about a person or individual. All humans have the ability to recognise individuals from their faces. Now following system is based on face recognition to maintain the attendance record of students. The daily attendance of students is recorded subject wise which is stored already by the administrator. As the time for corresponding subject arrives the system automatically starts taking snaps and then apply face detection and recognition technique to the given image and the recognize students are marked as present and their attendance update with corresponding time and subject id. We have used deep learning techniques to develop this system, histogram of oriented gradient method is used to detect faces in images and deep learning method is used to compute and compare facial feature of students to recognize them.

scholarly journals Masked Face Recognition Using Deep Learning: A Review

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2666
Author(s):  
Ahmad Alzu’bi ◽  
Firas Albalas ◽  
Tawfik AL-Hadhrami ◽  
Lojin Bani Bani Younis ◽  
Amjad Bashayreh
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Research Area ◽  
Network Architectures ◽  
Learning Techniques ◽  
Deep Feature ◽  
Deep Feature Extraction ◽  
Intelligent Models ◽  
Secure Authentication ◽  
Intelligent Process

A large number of intelligent models for masked face recognition (MFR) has been recently presented and applied in various fields, such as masked face tracking for people safety or secure authentication. Exceptional hazards such as pandemics and frauds have noticeably accelerated the abundance of relevant algorithm creation and sharing, which has introduced new challenges. Therefore, recognizing and authenticating people wearing masks will be a long-established research area, and more efficient methods are needed for real-time MFR. Machine learning has made progress in MFR and has significantly facilitated the intelligent process of detecting and authenticating persons with occluded faces. This survey organizes and reviews the recent works developed for MFR based on deep learning techniques, providing insights and thorough discussion on the development pipeline of MFR systems. State-of-the-art techniques are introduced according to the characteristics of deep network architectures and deep feature extraction strategies. The common benchmarking datasets and evaluation metrics used in the field of MFR are also discussed. Many challenges and promising research directions are highlighted. This comprehensive study considers a wide variety of recent approaches and achievements, aiming to shape a global view of the field of MFR.

Gastronomic Algorithms: Artistic and Sensory Exploration of Alain Passard's Michelin Plates in the Manner of Giuseppe Arcimboldo with GANs

Leonardo ◽  
2021 ◽  
pp. 1-11
Author(s):  
Emily L. Spratt
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Generative Adversarial Networks ◽  
Adversarial Networks ◽  
Artistic Collaboration ◽  
Recent Advances ◽  
Learning Techniques ◽  
Data Scientist ◽  
The Senses ◽  
Computer Programmer

Abstract Although recent advances in artificial intelligence to generate images with deep learning techniques, especially generative adversarial networks (GANs), have offered radically new opportunities for its creative applications, there has been little investigation into its use as a tool to explore the senses beyond vision alone. In an artistic collaboration that brought Chef Alain Passard, art historian and data scientist Emily Spratt, and computer programmer Thomas Fan together, photographs of the three-star Michelin plates from the Parisian restaurant Arpège were used as a springboard to explore the art of culinary presentation in the manner of the Renaissance painter Giuseppe Arcimboldo.

Sign in / Sign up

Export Citation Format

Share Document