37 citations · 48 across the 4 of their papers we have counts for
4 papers
Automatic Compiler Based FPGA Accelerator for CNN Training
Shreyas Kolala Venkataramanaiah, Yufei Ma, Shihui Yin +4
Training of convolutional neural networks (CNNs)on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hard-war…
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen +3
The computational demands of computer vision tasks based on state-of-the-art Convolutional Neural Network (CNN) image classification far exceed the energy budgets of mobile devices…
Minimizing Area and Energy of Deep Learning Hardware Design Using Collective Low Precision and Structured Compression
Shihui Yin, Gaurav Srivastava, Shreyas K. Venkataramanaiah +3
Deep learning algorithms have shown tremendous success in many recognition tasks; however, these algorithms typically include a deep neural network (DNN) structure and a large numb…
Algorithm and Hardware Design of Discrete-Time Spiking Neural Networks Based on Back Propagation with Binary Activations
Shihui Yin, Shreyas K. Venkataramanaiah, Gregory K. Chen +4
We present a new back propagation based training algorithm for discrete-time spiking neural networks (SNN). Inspired by recent deep learning algorithms on binarized neural networks…