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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

Product type Book
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Pages 380 pages
Edition 1st Edition
Languages
Authors (2):
Anubhav Singh Anubhav Singh
Profile icon Anubhav Singh
Rimjhim Bhadani Rimjhim Bhadani
Profile icon Rimjhim Bhadani
View More author details
Toc

Table of Contents (13) Chapters close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models 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 current research areas for DL in mobile apps

It is crucial for the healthy growth of any field of study that an active community of researchers invests time and effort into it. Fortunately, the application of DL on mobile devices has gathered strong attention from developers and researchers worldwide, with many mobile handset manufacturers, such as Samsung, Apple, Realme, and Xiaomi, integrating DL right into the system user interface (UI) they produce for all their devices. This gives a huge boost to the speed at which the models run, and their accuracy is regularly improved by system updates.

Let's look at some of the most popular research areas in the field and how they've been progressing.

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