A Gentle Introduction to Deep Learning for Face Recognition
Last Updated on July 5, 2019
Face recognition is the problem of identifying and verifying people in a photograph by their face.
It is a task that is trivially performed by humans, even under varying light and when faces are changed by age or obstructed with accessories and facial hair. Nevertheless, it is remained a challenging computer vision problem for decades until recently.
Deep learning methods are able to leverage very large datasets of faces and learn rich and compact representations of faces, allowing modern models to first perform as-well and later to outperform the face recognition capabilities of humans.
In this post, you will discover the problem of face recognition and how deep learning methods can achieve superhuman performance.
After reading this post, you will know:
- 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.
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