217 citations · 295 across the 7 of their papers we have counts for
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cs.AR2022
Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile
Renzo Andri, Beatrice Bussolino, Antonio Cipolletta +2
Most of today's computer vision pipelines are built around deep neural networks, where convolution operations require most of the generally high compute effort. The Winograd convol…
cs.AR2020★ 217 cited
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead
Maurizio Capra, Beatrice Bussolino, Alberto Marchisio +3
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to au…