1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2021★ 1 cited
Dense Pruning of Pointwise Convolutions in the Frequency Domain
Mark Buckler, Neil Adit, Yuwei Hu +2
Depthwise separable convolutions and frequency-domain convolutions are two recent ideas for building efficient convolutional neural networks. They are seemingly incompatible: the v…
cs.CV2018
EVA: Exploiting Temporal Redundancy in Live Computer Vision
Mark Buckler, Philip Bedoukian, Suren Jayasuriya +1
Hardware support for deep convolutional neural networks (CNNs) is critical to advanced computer vision in mobile and embedded devices. Current designs, however, accelerate generic…
cs.CV2017
Reconfiguring the Imaging Pipeline for Computer Vision
Mark Buckler, Suren Jayasuriya, Adrian Sampson
Advancements in deep learning have ignited an explosion of research on efficient hardware for embedded computer vision. Hardware vision acceleration, however, does not address the…