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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

Product type Paperback

Published in Jan 2018

Publisher Packt

ISBN-13 9781788295628

Length 310 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Computer Vision

Author (1):

Rajalingappaa Shanmugamani

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Table of Contents (12) Chapters

Preface

1. Getting Started FREE CHAPTER

2. Image Classification

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

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Summary

In this chapter, we have seen how to deploy the trained deep learning models on various platforms and devices. We have covered the steps as well as guidelines on getting the best performance for these platforms. We have seen the advantages of MobileNets for reducing the inference time with a small trade-off of accuracy.

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Authors (1)

Shanmugamani

Shanmugamani

Rajalingappaa Shanmugamani is currently working as an Engineering Manager for a Deep learning team at Kairos. Previously, he worked as a Senior Machine Learning Developer at SAP, Singapore and worked at various startups in developing machine learning products. He has a Masters from Indian Institute of TechnologyMadras. He has published articles in peer-reviewed journals and conferences and submitted applications for several patents in the area of machine learning. In his spare time, he coaches programming and machine learning to school students and engineers.

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