Deep Learning for Face Detection, Recognition & Aging

Deep Learning for Face Detection, Recognition & Aging, available at $19.99, has an average rating of 3, with 15 lectures, 1 quizzes, based on 12 reviews, and has 61 subscribers.

You will learn about To understand the architecture of deep learning models used for face detection, recognition, and aging To implement deep learning models used for face detection, recognition, and aging This course is ideal for individuals who are Individuals who are interested to know the architecture and implementation of deep learning models used for face detection, recognition, and aging. It is particularly useful for Individuals who are interested to know the architecture and implementation of deep learning models used for face detection, recognition, and aging.

Enroll now: Deep Learning for Face Detection, Recognition & Aging

Summary

Title: Deep Learning for Face Detection, Recognition & Aging

Price: $19.99

Average Rating: 3

Number of Lectures: 15

Number of Quizzes: 1

Number of Published Lectures: 15

Number of Published Quizzes: 1

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

To understand the architecture of deep learning models used for face detection, recognition, and aging
To implement deep learning models used for face detection, recognition, and aging

Who Should Attend

Individuals who are interested to know the architecture and implementation of deep learning models used for face detection, recognition, and aging.

Target Audiences

Individuals who are interested to know the architecture and implementation of deep learning models used for face detection, recognition, and aging.

This is in-depth short course that deeply overviews and explains the architecture of deep learning models that were proposed in the literature for face detection, recognition, and aging. In addition, this course presents the detailed steps for Python code that used to build these deep models.

All the development tools and materials required for this course are FREE. Besides that, all implemented Python codes are attached with this course.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Face Detection

Lecture 1: Overview of MTCNN Architecture

Lecture 2: Overview of P-Net

Lecture 3: Overview of CNN Operations

Lecture 4: Overview R-Net & O-Net

Lecture 5: Python Implementation of MTCNN

Lecture 6: MTCNN Tuning

Chapter 3: Video-based Face Detection and Tracking

Lecture 1: Face_Detection_and_Tracking

Lecture 2: Demo

Chapter 4: Evaluation of Face Detection

Lecture 1: Evaluation of Face Detection

Chapter 5: Face Recognition

Lecture 1: Overview of FaceNet Architecture

Lecture 2: Triplet Loss Learning

Lecture 3: Python Implementation

Chapter 6: Face Aging

Lecture 1: Overview of Face Aging Models

Lecture 2: Training and Testing Models

Instructors

Hussein Samma
Assistant Professor

Rating Distribution

1 stars: 3 votes
2 stars: 1 votes
3 stars: 3 votes
4 stars: 2 votes
5 stars: 3 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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