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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

Summary

In this chapter, we examined the concept behind image processing and how we can integrate it with our Android- or iOS-based application made using Flutter to perform face detection. The chapter started with adding relevant dependencies to support the functionalities of Firebase ML Kit and the image_picker library. The required UI components with the necessary functionalities were added. The implementation mainly covered image file selection using the Flutter plugin and how images can be processed once they are selected. An example of on-device Face Detector model usage was presented, along with an in-depth discussion of the method by which the implementation was carried out. 

In the next chapter, we will be discussing how you can create your own AI-powered chatbot that can double-up as a virtual assistant using the Actions on Google platform.&...

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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
Published in: Apr 2020 Publisher: Packt ISBN-13: 9781789611212
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