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Found 2 papers, 2 papers with code
DNN Feature Map Compression using Learned Representation over GF(2)
In this paper, we introduce a method to compress intermediate feature maps of deep neural networks (DNNs) to decrease memory storage and bandwidth requirements during inference.
ShiftCNN: Generalized Low-Precision Architecture for Inference of Convolutional Neural Networks
In this paper we introduce ShiftCNN, a generalized low-precision architecture for inference of multiplierless convolutional neural networks (CNNs).
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