Deep Learning on Images

The concept of edge detection was covered in Chapter 1, Computer Vision and TensorFlow Fundamentals. In this chapter, you will learn how edge detection is used to create convolution operations over volume and how different convolution parameters such as filter size, dimensions, and operation type (convolution versus pooling) affect the convolution volume (width versus depth). This chapter will give you a very detailed overview of how a neural network sees an image and how it uses that visualization to classify images. You will start by building your first neural network and then visualize an image as it goes through its different layers. You will then compare the network model's accuracy and visualization to an advanced network such as VGG 16 or Inception.