11 citations · 24 across the 7 of their papers we have counts for
3 papers · 1 filter
Subtensor Quantization for Mobilenets
Thu Dinh, Andrey Melnikov, Vasilios Daskalopoulos +1
Quantization for deep neural networks (DNN) have enabled developers to deploy models with less memory and more efficient low-power inference. However, not all DNN designs are frien…
Bit Efficient Quantization for Deep Neural Networks
Prateeth Nayak, David Zhang, Sek Chai
Quantization for deep neural networks have afforded models for edge devices that use less on-board memory and enable efficient low-power inference. In this paper, we present a comp…
Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines
Kilho Son, Jesse Hostetler, Sek Chai
Complex image processing and computer vision systems often consist of a processing pipeline of functional modules. We intend to replace parts or all of a target pipeline with deep…