Details about Deep Learning for Vision Systems
Deep Learning for Vision Systems PDF free download – This book is structured into three parts. The first part explains deep leaning in detail as a foundation for the remaining topics. I strongly recommend that you not skip this section, because it dives deep into neural network components and definitions and explains all the notions required to be able to understand how neural networks work under the hood. After reading part 1, you can jump directly to topics of interest in the remaining chapters. Part 2 explains deep learning techniques to solve object classification and detection problems, and part 3 explains deep learning techniques to generate images and visual embeddings. In several chapters, practical projects implement the topics discussed.
All of this book’s code examples use open source frameworks that are free to download. We will be using Python, Tensorflow, Keras, and OpenCV. Appendix A walks you through the complete setup. I also recommend that you have access to a GPU if you want to run the book projects on your machine, because chapters 6–10 contain more complex projects to train deep networks that will take a long time on a regular CPU. Another option is to use a cloud environment like Google Colab for free or other paid options. Examples of source code occur both in numbered listings and in line with normal text. In both cases, source code is formatted in a fixed-width font like this to separate it from ordinary text. Sometimes code is also in bold to highlight code that has changed from previous steps in the chapter, such as when a new feature adds to an existing line of code.