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Deep Learning: masked face detection, recognition

SSD face and facial mask detection, and train your own model to recognize faces even with masks
4.6
4.6/5
(41 reviews)
209 students
Created by

9.8

Classbaze Grade®

10.0

Freshness

9.4

Popularity

9.5

Material

SSD face and facial mask detection
Platform: Udemy
Video: 12h 9m
Language: English
Next start: On Demand

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Classbaze Rating

Classbaze Grade®

9.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

10.0 / 10
This course was last updated on 5/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

9.4 / 10
We analyzed factors such as the rating (4.6/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

9.5 / 10
Video Score: 9.4 / 10
The course includes 12h 9m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 8 hours 18 minutes of 153 Deep Learning courses on Udemy.
Detail Score: 9.5 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
40 resources.
0 exercise.
0 test.

In this page

About the course

Deep Learning of artificial intelligence(AI) is an exciting future technology with explosive growth.
Masked face recognition is a mesmerizing topic which contains several AI technologies including classifications, SSD object detection, MTCNN, FaceNet, data preparation, data cleaning, data augmentation, training skills, etc.
Nowadays, people are required to wear masks due to the COVID-19 pandemic.
The conventional FaceNet model barely recognizes faces without masks
Even the FaceID on iPhone or iPad devices only works without masks.
In this course, I will teach you how to train a model that works with masks.
In the final presentation, you will be able to perform the real time face detection, face mask detection, and face recognition, even with masks!
Windows is the operating system so you don’t need to learn Linux first.
Having Python and Tensorflow knowledge are required.
In my tutorials, I would like to explain difficult theories and formulas by easy concepts or practical examples.
Model training always takes a lot of time.
Take this project as an example, it needs more than 400,000 images to train.
I will offer training skills to speed up the training process.
These training skills can be not only applied in face recognition but also in your future projects.
All lectures are spoken in plain English.
If you feel my speaking pace is quite slow, you can use the gear setting to speed up.
If you don’t want to train the model by yourself, the source code and trained weight files are included!
Besides the training steps, this is also a highly integrated application.
Achievement from the topic, skills grow from the project. I hope you enjoy the fun of AI.

What can you learn from this course?

✓ How to install Python, Tensorflow, Pycharm from scratch
✓ How to create your own classification model
✓ What’s FaceNet
✓ What’s the difference between classification models and face recognition models
✓ How to create your own FaceNet model by modifying the classification model
✓ How to do the face alignment using SSD face detection
✓ How to do the face alignment using MTCNN face detection
✓ How to do the data cleaning
✓ How to create masked face dataset
✓ How to train your FaceNet model
✓ What are training skills
✓ How to implement training skills to train models effectively
✓ How to perform the real time face detection, mask detection, and face recognition

What you need to start the course?

• High school mathematics level
• Basic Python and Tensorflow
• Desktop or laptop with Windows and at least 6GB Nvidia GPU cards
• A USB camera or a laptop camera

Who is this course is made for?

• Those who have Python basics tend to learn Deep Learning or Face Recognition
• Any engineers who want to level up in Deep Learning

Are there coupons or discounts for Deep Learning: masked face detection, recognition ? What is the current price?

The course costs $129.99.
The average price is $16.2 of 153 Deep Learning courses. So this course is -702% cheaper than the average Deep Learning course on Udemy.

Will I be refunded if I'm not satisfied with the Deep Learning: masked face detection, recognition course?

YES, Deep Learning: masked face detection, recognition has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

At the moment we could not find an available financial aid for Deep Learning: masked face detection, recognition.

Who will teach this course? Can I trust Johnny Liao?

Johnny Liao has created 1 courses that got 41 reviews which are generally positive. Johnny Liao has taught 209 students and received a 4.6 average review out of 41 reviews. Depending on the information available, we think that Johnny Liao is an instructor that you can trust.
AI computer vision algorithm engineer
Johnny has a MS in electrical engineering from National Central University in Taiwan.
He used to be a cellphone hardware engineer in Hon Hai Technology Group.
For the interest of coding, he learned C and Python by self-study.
He completed IOT Wifi and Zigbee systems applied in TSMC, Arcadyan, Delta, Mitac, and ITRI.
With the explosive growth of AI, he learned AI basics by self-study.
He has been a full-time AI computer vision engineer since he left previous firmware system engineer job several years ago.
Browse all courses by on Classbaze.

9.8

Classbaze Grade®

10.0

Freshness

9.4

Popularity

9.5

Material

Platform: Udemy
Video: 12h 9m
Language: English
Next start: On Demand

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