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Deep Learning: masked face detection, recognition


Deep Learning: masked face detection, recognition

Deep Learning: masked face detection, recognition SSD face and facial mask detection, MTCNN face detection, and train your own model to recognize faces even with masks

What you'll learn

  • How to install Python, Tensorflow, Pycharm from scratch
  • What's the difference between classification models and face recognition models
  •  time face detection, mask detection, and face recognition

Requirements

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

Description

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 very proudly perform the real time face detection, face mask detection, and face recognition, even with masks!
  • Windows is the operating system so you will not need to learn Linux first.
  • I will instruct you to install Python, Tensorflow, and Pycharm IDE from scratch.
  • Having basic Python and Tensorflow knowledge will be an advantage, but if not, I will have a quick guide to both for you.
  • 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've spent much time on training skills.

  • After numerous experimental confirmation, I summarized my methods by plots to let you digest easily.
  • These training skills can be not only applied in face recognition but also in other models.
  • 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.
  • The auto-generated captions may have errors. I will review and correct them.
  • Achievement from the topic, skills grow from the project. I hope you enjoy the fun of AI.

Online Course CoupoNED
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