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Simon Narduzzi

2 accepted papers

2022

Optimizing The Consumption Of Spiking Neural Networks With Activity Regularization

ICASSP 2022accepted

Reducing energy consumption is a critical point for neural network models running on edge devices. In this regard, reducing the number of multiply-accumulate (MAC) operations of Deep Neural Networks (DNNs) running on edge hardware accelerators will reduce the energy consumption during inference. Spi…

Cited by 0Source ↗Scholar ↗
2020

Efficient Neural Vision Systems Based on Convolutional Image Acquisition

CVPR 2020oral

Despite the substantial progress made in deep learning in recent years, advanced approaches remain computationally intensive. The trade-off between accuracy and computation time and energy limits their use in real-time applications on low power and other resource-constrained systems. In this paper,…

Cited by 30PDF ↗Scholar ↗