298 citations · 306 across the 2 of their papers we have counts for
2 papers
cs.LG2017★ 8 cited
ADaPTION: Toolbox and Benchmark for Training Convolutional Neural Networks with Reduced Numerical Precision Weights and Activation
Moritz B. Milde, Daniel Neil, Alessandro Aimar +2
Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) are useful for many practical tasks in machine learning. Synaptic weights, as well as neuron activation functio…
cs.CV2017★ 298 cited
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Alessandro Aimar, Hesham Mostafa, Enrico Calabrese +8
Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many state-of-the-art (SOA) visual processing tasks. Even though Graphical Pro…