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Face Recognition

Introduction to Face Recognition with Tensorflow Blazeface ML Model:

Face recognition models in Deep and Machine Learning are primarily created to ensure the security of identity. There are several frameworks used in building a face recognition model and one of them is TensorFlow. The TensorFlow face recognition model has so far proven to be popular.

When you hear "face recognition system", what comes first to your mind? Let me guess. Your smartphone's security lock? Nam Do San?

Every smartphone we know is run on a system of algorithms that match human faces against a database of faces for user authentication. Yours cannot be different.

Aside from smartphones, face recognition systems can be found in other forms of technology such as robotics and facial biometrics. You may find its uses in surveillance videos, indexing, and technologies that require increased human-computer interaction.

In essence, we are saying the face recognition system you see everywhere is a product of Machine Learning in Artificial Intelligence. Its major function is to map facial features automatically with varying degrees of accuracy. Being related to AI, the system works through a series of algorithms and computational models.

For a fuller understanding of how a face recognition system works, we should look at its different applications.

Tools:

  • Tensorflow.js [Tensorflow Blazeface Model]
  • HTML5
  • CSS3
  • JavaScript ES6+

Planning:

I am planning to migrate it in React, or add different tensorflow models and make a button with a dropdowm where the visitor can choose.