Hello trend,
This is Satya Mallick from LearnOpenCV.com.
In today's article, we will understand the concept of Facial Emotion Recognition from both a philosophical and technical point of view. We will also explore a custom VGG13 model architecture and the revolutionary Face Expression Recognition Plus (FER+) dataset to build a consolidated real-time facial emotion recognition system.
Check out our latest tutorial to understand how to implement Emotion Recognition using OpenCV
| Facial Emotion Recognition with OpenCV |
The accompanying code for the blog post can be found here:
| Download Code |
If you want to learn more about Face Detection, Face Recognition, and face-related applications, I'm sharing a list of resources that might be helpful for you:
- Face Detection - The Ultimate Guide
- Advances in Face Recognition Models
- Creating SnapChat Filters
- Drowsiness Detection using Mediapipe
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| Join OpenCV University |
What are the students saying?
As teachers of the craft of AI, we love the following quote
We got reminded of this quote when Daniel Schaben tagged us in a tweet with his certificate of completion for Computer Vision I.
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Thank you, Daniel, for those beautiful words. Wholly unsolicited and straight from the heart. Priceless!
Here is another post from Israel Raul Tiñini Alvarez who tagged on his LinkedIn post with his certificate of completion.
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The comment was heartwarming because Israel not only called our courses the "best courses in computer vision and image processing," he also called the material intuitive.
We teach because it is very satisfying to see students in our course gain a deep understanding of the material while embarking on a financially rewarding career path. What starts as a spark of interest becomes a blazing fire.
You have 30 days to change your mind with our 30-day no-questions-asked money-back guarantee. You get to keep the book even if you change your mind!
| Join OpenCV University |
Cheers,
Satya
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