98 citations · 107 across the 4 of their papers we have counts for
4 papers
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…
DDD17: End-To-End DAVIS Driving Dataset
Jonathan Binas, Daniel Neil, Shih-Chii Liu +1
Event cameras, such as dynamic vision sensors (DVS), and dynamic and active-pixel vision sensors (DAVIS) can supplement other autonomous driving sensors by providing a concurrent s…
Sensor Transformation Attention Networks
Stefan Braun, Daniel Neil, Enea Ceolini +2
Recent work on encoder-decoder models for sequence-to-sequence mapping has shown that integrating both temporal and spatial attention mechanisms into neural networks increases the…
Steering a Predator Robot using a Mixed Frame/Event-Driven Convolutional Neural Network
Diederik Paul Moeys, Federico Corradi, Emmett Kerr +5
This paper describes the application of a Convolutional Neural Network (CNN) in the context of a predator/prey scenario. The CNN is trained and run on data from a Dynamic and Activ…