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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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Image Captioning

In this chapter, we will deal with the problem of captioning images. This involves detecting the objects and also coming up with a text caption for the image. Image captioning also can be called Image to Text translation. Once thought a very tough problem, we have reasonably good results on this now. For this chapter, a dataset of images with corresponding captions is required. In this chapter, we will discuss the techniques and applications of image captioning in detail.

We will cover the following topics in this chapter:

  • Understand the different datasets and metrics used to evaluate them
  • Understand some techniques used for natural language processing problems
  • Different words for vector models
  • Several algorithms for image captioning
  • Adverse results and scope for improvement
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