A Cloud-Edge-Smart IoT Architecture for Speeding Up the Deployment of Neural Network Models with Transfer Learning Techniques

A Cloud-Edge-Smart IoT Architecture for Speeding Up the Deployment of Neural Network Models with Transfer Learning Techniques

Existing edge computing architectures do not support the updating of neural network models, nor are they optimized for storing, updating, and transmitting different neural network models to a large number of IoT devices. In this paper, a cloud-edge smart IoT architecture for speeding up the deployme...

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Bibliographic Details
Main Authors: Tz-Heng Hsu, Zhi-Hao Wang, Aaron Raymond See
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Electronics
Subjects:
deep learning
transfer learning
lightweight neural network
edge computing
Online Access:https://www.mdpi.com/2079-9292/11/14/2255

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https://www.mdpi.com/2079-9292/11/14/2255

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