50 citations · 111 across the 9 of their papers we have counts for
5 papers · 1 filter
A Resource-Efficient Embedded Iris Recognition System Using Fully Convolutional Networks
Hokchhay Tann, Heng Zhao, Sherief Reda
Applications of Fully Convolutional Networks (FCN) in iris segmentation have shown promising advances. For mobile and embedded systems, a significant challenge is that the proposed…
Flexible Deep Neural Network Processing
Hokchhay Tann, Soheil Hashemi, Sherief Reda
The recent success of Deep Neural Networks (DNNs) has drastically improved the state of the art for many application domains. While achieving high accuracy performance, deploying s…
Hardware-Software Codesign of Accurate, Multiplier-free Deep Neural Networks
Hokchhay Tann, Soheil Hashemi, Iris Bahar +1
While Deep Neural Networks (DNNs) push the state-of-the-art in many machine learning applications, they often require millions of expensive floating-point operations for each input…
Understanding the Impact of Precision Quantization on the Accuracy and Energy of Neural Networks
Soheil Hashemi, Nicholas Anthony, Hokchhay Tann +2
Deep neural networks are gaining in popularity as they are used to generate state-of-the-art results for a variety of computer vision and machine learning applications. At the same…
Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off
Hokchhay Tann, Soheil Hashemi, R. Iris Bahar +1
We present a novel dynamic configuration technique for deep neural networks that permits step-wise energy-accuracy trade-offs during runtime. Our configuration technique adjusts th…