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Face Recognition and Analysis

10,000.00

( 0 Review )

Course Level

Intermediate

Video Tutorials

17

Course content

Week 1-2: Introduction to Computer Vision and Deep Learning

Overview of computer vision and deep learning applications
Convolutional neural networks (CNN) and backpropagation algorithm
Hands-on exercises on building and training deep learning models in TensorFlow or PyTorch

Week 3-4: Facial Features Detection and Tracking

Week 5-6: Face Recognition with Traditional Methods

Week 7-8: Deep Learning for Face Recognition

Week 9-10: Face Recognition in the Wild

Week 11-12: Advanced Topics and Project Work

About Course

Face recognition and analysis is a technology that involves the identification, verification, and analysis of a person’s face using computer algorithms. It uses a combination of hardware and software tools to capture and process an image of a person’s face, and then compare it with a database of stored images to determine if there is a match.

Face recognition and analysis have a wide range of applications, including security systems, law enforcement, biometric authentication, and marketing research. In security systems, face recognition can be used to identify individuals for access control, monitor crowds for suspicious behavior, and detect known criminals in public places. In law enforcement, it can be used to help identify suspects in criminal investigations.

In biometric authentication, face recognition can be used as a secure and convenient way to unlock devices, make payments, and access accounts. In marketing research, face recognition can be used to analyze facial expressions and emotions, providing insights into consumer behavior and preferences.

The technology behind face recognition and analysis is constantly evolving, with ongoing research and development aimed at improving its accuracy, speed, and reliability. However, it also raises concerns about privacy and surveillance, and its use is subject to regulations and laws in many jurisdictions.

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Material Includes

  • Live Classes
  • 100% Online Course
  • Hands-on Project
  • Shareable Certificate

Instructor

JG
0 /5

20 Courses

AG
4.44 /5

78 Courses

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Material Includes

  • Live Classes
  • 100% Online Course
  • Hands-on Project
  • Shareable Certificate

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