Machine Learning

9 Applications of Deep Learning for Computer Vision

Last Updated on July 5, 2019

The field of computer vision is shifting from statistical methods to deep learning neural network methods.

There are still many challenging problems to solve in computer vision. Nevertheless, deep learning methods are achieving state-of-the-art results on some specific problems.

It is not just the performance of deep learning models on benchmark problems that is most interesting; it is the fact that a single model can learn meaning from images and perform vision tasks, obviating the need for a pipeline of specialized and hand-crafted methods.

In this post, you will discover nine interesting computer vision tasks where deep learning methods are achieving some headway.

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Overview

In this post, we will look at the following computer vision problems where deep learning has been used:

  1. Image Classification
  2. Image Classification With Localization
  3. Object Detection
  4. Object Segmentation
  5. Image Style Transfer
  6. Image Colorization
  7. Image Reconstruction
  8. Image Super-Resolution
  9. Image Synthesis
  10. Other Problems

Note, when it comes to the image classification (recognition) tasks, the naming convention from the ILSVRC has been
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