Getting Started With Hybrid Edge AI for Facial Recognition

Sergey L. Gladkiy

Rate me:

4.73/5 (4 votes)

16 Jul 2021CPOL4 min read

6.6K

426

In this article we discuss the principles of face detection and facial recognition.

Here we state the problem of face recognition using AI and Edge devices. Then list the main steps: detection, alignment, feature extraction, and identification. And finally, give a short outline of the series and state the tools we’ll use: Python, MTCNN, Keras with TensorFlow, OpenCV, FaceNet.

Views

Daily Counts

Downloads

Weekly Counts

This article is part of the series 'Hybrid Edge AI for Facial Recognition View All Next ▷

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Sergey L. Gladkiy

Team Leader VIPAKS

Russian Federation

EDUCATION:

Master’s degree in Mechanics.

PhD degree in Mathematics and Physics.

PROFESSIONAL EXPERIENCE:

15 years’ experience in developing scientific programs
(C#, C++, Delphi, Java, Fortran).

SCIENTIFIC INTERESTS:

Mathematical modeling, symbolic computer algebra, numerical methods, 3D geometry modeling, artificial intelligence, differential equations, boundary value problems.

Getting Started With Hybrid Edge AI for Facial Recognition

Views

Downloads

License

Comments and Discussions