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Deep Learning for Computer Vision

You're reading from   Deep Learning for Computer Vision Expert techniques to train advanced neural networks using TensorFlow and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788295628
Length 310 pages
Edition 1st Edition
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Author (1):
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Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started 2. Image Classification FREE CHAPTER 3. Image Retrieval 4. Object Detection 5. Semantic Segmentation 6. Similarity Learning 7. Image Captioning 8. Generative Models 9. Video Classification 10. Deployment 11. Other Books You May Enjoy

Detecting objects in an image


Object detection had an explosion concerning both applications and research in recent years. Object detection is a problem of importance in computer vision. Similar to image classification tasks, deeper networks have shown better performance in detection. At present, the accuracy of these techniques is excellent. Hence it used in many applications.

Image classification labels the image as a whole. Finding the position of the object in addition to labeling the object is called object localization. Typically, the position of the object is defined by rectangular coordinates. Finding multiple objects in the image with rectangular coordinates is called detection. Here is an example of object detection:

The image shows four objects with bounding boxes. We will learn algorithms that can perform the task of finding the boxes. The applications are enormous in robot vision, such as self-driving cars and industrial objects. We can summarize localization and detection tasks...

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