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Found 2 papers, 1 papers with code
HCM: Hardware-Aware Complexity Metric for Neural Network Architectures
Convolutional Neural Networks (CNNs) have become common in many fields including computer vision, speech recognition, and natural language processing.
Feature Map Transform Coding for Energy-Efficient CNN Inference
We analyze the performance of our approach on a variety of CNN architectures and demonstrate that FPGA implementation of ResNet-18 with our approach results in a reduction of around 40% in the memory energy footprint, compared to quantized network, with negligible impact on accuracy.
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