This post is a part of a medium based ‘A Layman’s guide to Deep Learning’ series that I plan to publish in an incremental fashion. The target audience is beginners with basic programming skills; preferably Python.
This post assumes you have a basic understanding of Deep Neural Networks a.k.a. Feed-forward neural networks. A detailed post covering this has been published in the previous post — A Layman’s guide to Deep Neural Networks. Reading the previous post is highly recommended for a better understanding of this post.
‘Computer Vision’ as a field has evolved to new heights with the advent of deep learning. The ability to aid machines in comprehending the details of an image in a more intuitive way than siloed pixel values or few hand-crafted features has brought a paradigm shift in the field. Today, a breadth of cutting-edge computer vision applications are used in our daily life commercial as well as enterprise and industrial tech products. We have been recipients of colossal benefits from in our casual life from the recent advances of deep learning in computer vision; you might have missed on recognizing the details of the application of the field in some products. Few notable examples are, the auto-pilot mode in Tesla, the face-id unlock, Animoji and advanced camera features in iPhones, the bokeh effect (portrait mode) in your smartphone camera, filters in Snapchat and Facebook messengers, etc.