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Face Detection In Machine Learning

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Face Recognition

Face recognition is the problem that is used to computer vision and image processing task. It works as per below  methods:

  • Face recognition is a broad problem of identifying or verifying people in photographs and videos.

  • Face recognition is a process comprised of detection, alignment, feature extraction, and a recognition task

  • Deep learning models first approached then exceeded human performance for face recognition tasks.

Face Recognition divided into below categories:

  • Faces in Photographs

  • Process of Automatic Face Recognition

  • Face Detection Task

  • Face Recognition Tasks

  • Deep Learning for Face Recognition

Face Detection

As per above definition we can easily identify that it is the part of face recognition. Face detection applications use algorithms and ML to find human faces within larger images, which often incorporate other non-face objects such as landscapes, buildings and other human body parts like feet or hands

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Techniques Used In Face Detection

  • Removing the background: used to change the image background and border of images.

  • Identifying face by color: sometimes skin color can be used to find faces; however, this may not work with all complexions.

  • Detect the face in motion: In real-time video, a face is almost always moving, so users of this method must calculate the moving area. One drawback of this method is the risk of confusion with other objects moving in the background.

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