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Hands-On Deep Learning for IoT

You're reading from   Hands-On Deep Learning for IoT Train neural network models to develop intelligent IoT applications

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781789616132
Length 308 pages
Edition 1st Edition
Languages
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Authors (3):
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Aditya Trivedi Aditya Trivedi
Author Profile Icon Aditya Trivedi
Aditya Trivedi
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Dr. Mohammad Abdur Razzaque Dr. Mohammad Abdur Razzaque
Author Profile Icon Dr. Mohammad Abdur Razzaque
Dr. Mohammad Abdur Razzaque
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: IoT Ecosystems, Deep Learning Techniques, and Frameworks FREE CHAPTER
2. The End-to-End Life Cycle of the IoT 3. Deep Learning Architectures for IoT 4. Section 2: Hands-On Deep Learning Application Development for IoT
5. Image Recognition in IoT 6. Audio/Speech/Voice Recognition in IoT 7. Indoor Localization in IoT 8. Physiological and Psychological State Detection in IoT 9. IoT Security 10. Section 3: Advanced Aspects and Analytics in IoT
11. Predictive Maintenance for IoT 12. Deep Learning in Healthcare IoT 13. What's Next - Wrapping Up and Future Directions 14. Other Books You May Enjoy

Summary

The healthcare industry is adopting ML and DL for various applications. IoT healthcare applications need to adopt ML and DL techniques for the true realization of healthcare IoT. In this chapter, we have tried to show how DL-based IoT solutions can be useful and how they can be implemented in healthcare applications. In the first part of this chapter, we presented an overview of the various applications of IoT in healthcare. Then, we briefly discussed two use cases where healthcare services can be improved and/or automated through DL-supported IoT solutions. In the second part of the chapter, we presented a hands-on experience of the DL-based healthcare incident and/or skin diseases, detection part of the two use cases.

The use of DL in IoT applications is emerging. However, there are challenges associated with DL techniques and IoT that need to be addressed soon in order...

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