In this chapter, we shall discuss recent advances in image processing with deep learning. We'll start by differentiating between classical and deep learning techniques, followed by a conceptual section on convolutional neural networks (CNN), the deep neural net architectures particularly useful for image processing. Then we'll continue our discussion on the image classification problem with a couple of image datasets and how to implement it with TensorFlow and Keras, two very popular deep learning libraries. Also, we'll see how to train deep CNN architectures and use them for predictions.

 The topics to be covered in this chapter are as follows:

• Deep learning in image processing
• CNNs
• Image classification with TensorFlow or Keras with the handwritten digits images dataset
• Some popular deep CNNs (VGG-16/19, InceptionNet, ResNet) with an application in classifying the cats versus dogs images with the VGG-16 network