most citedAutomated flow for compressing convolution neural networks for efficient edge-computation with FPGA

3 citations · 3 across the 1 of their papers we have counts for

collaborators

2 papers

cs.CV2019

Accelerating Training using Tensor Decomposition

Mostafa Elhoushi, Ye Henry Tian, Zihao Chen +2

Tensor decomposition is one of the well-known approaches to reduce the latency time and number of parameters of a pre-trained model. However, in this paper, we propose an approach…

cs.AR2017★ 3 cited

Automated flow for compressing convolution neural networks for efficient edge-computation with FPGA

Farhan Shafiq, Takato Yamada, Antonio T. Vilchez +1

Deep convolutional neural networks (CNN) based solutions are the current state- of-the-art for computer vision tasks. Due to the large size of these models, they are typically run…