DFTS: Deep Feature Transmission Simulator

Resource type
Date created
2018-06-22
Authors/Contributors
Abstract
Collaborative intelligence is a deployment paradigm for deep AI models where some of the layers run on the mobile terminal or network edge, while others run in the cloud. In this scenario, features computed in the model need to be transferred between the edge and the cloud over an imperfect channel. Here we present a simulator to help study the effects of imperfect packet-based transmission of deep features. Our simulator is implemented in Keras and allows users to study the effects of both lossy packet transmission and quantization on the accuracy.
Document
Published as
H. Unnibhavi, H. Choi, S. R. Alvar, and I. V. Bajic, "DFTS: Deep Feature Transmission Simulator," IEEE Multimedia Signal Processing Workshop (MMSP), Vancouver, BC, Aug. 2018.
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Copyright is held by the author(s).
Scholarly level
Peer reviewed?
Yes
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Member of collection
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main.pdf 165.38 KB