BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems

摘要

The emergence of various intelligent mobile applications demands the deployment of powerful deep learning models at resource-constrained mobile devices. The device-edge co-inference framework provides a promising solution by splitting a neural network at