Face Recognition Method Using Deep Learning: Project Outline
The COVID-19 pandemic has caused unprecedented changes to the way we live our lives, from the way we interact with each other to the way we conduct business. As a result, organizations are increasingly adopting methods to facilitate contactless access to their premises and services, such as the use of digital identification and authentication technologies. One such technology, which has become increasingly popular in the last few months, is masked face recognition. Masked face recognition is a biometric authentication technology that uses digital images of an individual’s face, even when they are wearing a face mask. This technology has the potential to provide a secure and efficient method of authentication that can be used in a variety of scenarios during the COVID-19 pandemic. In this paper, we present a method of masked face recognition that can be used to provide efficient and secure access control during the COVID-19 pandemic. Our method utilizes a combination of deep learning-based facial recognition algorithms and mask detection algorithms to achieve accurate and efficient authentication. We also discuss the potential benefits and challenges associated with using this technology during the pandemic.
Applications
- Healthcare: In healthcare settings, identifying patients and healthcare workers wearing masks can help ensure proper treatment and safety protocols are followed.
- Law enforcement: Masked face recognition can be used by law enforcement agencies to identify individuals in public areas, such as airports or train stations, where masks may be required for health and safety reasons.
- Retail: In retail settings, masked face recognition can be used to identify customers who are wearing masks and customize their shopping experience.
- Education: In educational settings, masked face recognition can help identify students and staff who are wearing masks and ensure compliance with health and safety guidelines.
- Entertainment: In the entertainment industry, masked face recognition can be used to identify actors or performers who are wearing masks during rehearsals or performances.
Requirements
Hardware requirement
A laptop with:
- A CPU with clock speed of atleast 2.5GHz.
- GPU(atleast 4GB VRAM).
- RAM (more than 8GB ).
- SSD (more than 256GB)
Software requirement
- Python programming language
- Anaconda
- TensorFlow
- Keras
- OpenCV
Tool:
IDLE is an integrated development environment for Python, which has been bundled with the default implementation of the language since 1.5.2b1. It is packaged as an optional part of the Python packaging with many Linux distributions. It is completely written in Python and the Tkinter GUI toolkit.
Technology:
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
What you’ll Learn after doing this project ?
- Understand the concept of face recognition and its applications.
- Understand the concept of deep learning and its application in facial recognition.
- Learn how to develop a Masked Face Recognition method using a Convolutional Neural Network.
- Learn how to evaluate the performance of the developed Masked Face Recognition method.
