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Deep Learning for Computer Vision

Deep Learning for Computer Vision

By : Shanmugamani
3.2 (22)
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Deep Learning for Computer Vision

Deep Learning for Computer Vision

3.2 (22)
By: Shanmugamani

Overview of this book

Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation.
Table of Contents (12 chapters)
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Summary

In this chapter, we have covered the basics of deep learning. The vocabulary introduced in this chapter will be used throughout this book, hence, you can refer back to this chapter often. The applications of computer vision are also shown with examples. Installations of all the software packages for various platforms for the development environment were also covered.

In the next chapter, we will discuss how to train classification models using both Keras and TensorFlow on a dataset. We will look at how to improve the accuracy using a bigger model and other techniques such as augmentation, and fine-tuning. Then, we will see several advanced models proposed by several people around the world, achieving the best accuracy in competitions. 

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