Abstract

Convolutional Neural Network (CNN) models are widely used for image/video recognition tasks on mobile devices. The CNN is split into two parts - the computation-intensive and energy-intensive parts are offloaded to a network server while the privacy-sensitive and delay-sensitive parts are maintained at the end device. Techniques described herein allow a network to control the split for a user device in artificial intelligence (AI)/machine learning (ML) rendering based on a number of factors.

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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