18 citations · 73 across the 14 of their papers we have counts for
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cs.LG2019
Neural Network Training with Approximate Logarithmic Computations
Arnab Sanyal, Peter A. Beerel, Keith M. Chugg
The high computational complexity associated with training deep neural networks limits online and real-time training on edge devices. This paper proposed an end-to-end training and…
cs.CV2019★ 5 cited
A Pre-defined Sparse Kernel Based Convolution for Deep CNNs
Souvik Kundu, Saurav Prakash, Haleh Akrami +2
The high demand for computational and storage resources severely impede the deployment of deep convolutional neural networks (CNNs) in limited-resource devices. Recent CNN architec…
eess.IV2019
Machine Learning Based Image Calibration for a Twofold Time-Interleaved High Speed DAC
Daniel Beauchamp, Keith M. Chugg
In this paper, we propose a novel image calibration algorithm for a twofold time-interleaved DAC (TIDAC). The algorithm is based on simulated annealing, which is often used in the…