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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

You're reading from   Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter Build scalable real-world projects to implement end-to-end neural networks on Android and iOS

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Length 380 pages
Edition 1st Edition
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Authors (2):
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Rimjhim Bhadani Rimjhim Bhadani
Author Profile Icon Rimjhim Bhadani
Rimjhim Bhadani
Anubhav Singh Anubhav Singh
Author Profile Icon Anubhav Singh
Anubhav Singh
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models FREE CHAPTER 3. Chatbot Using Actions on Google 4. Recognizing Plant Species 5. Generating Live Captions from a Camera Feed 6. Building an Artificial Intelligence Authentication System 7. Speech/Multimedia Processing - Generating Music Using AI 8. Reinforced Neural Network-Based Chess Engine 9. Building an Image Super-Resolution Application 10. Road Ahead 11. Other Books You May Enjoy Appendix

Exploring the latest developments in DL on mobile devices

With the complexities of DL and AI combining with mobile applications, software and hardware optimizations are being constantly made to run the models efficiently on devices. Let's look at some of them.

Google's MobileNet

Google's MobileNet was launched in 2017. It is a set of mobile-first computer vision models based on TensorFlow, very carefully optimized to run efficiently within a restrictive mobile environment. It acts as a bridge between accuracy in complex neural network structures and performance constraints on mobile runtimes. Since the models have the capability to run locally on the device itself, MobileNet has the advantages of security,...

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