211 citations · 319 across the 4 of their papers we have counts for
4 papers
Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks
Bodo Rueckauer, Iulia-Alexandra Lungu, Yuhuang Hu +1
Deep convolutional neural networks (CNNs) have shown great potential for numerous real-world machine learning applications, but performing inference in large CNNs in real-time rema…
Deep counter networks for asynchronous event-based processing
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer
Despite their advantages in terms of computational resources, latency, and power consumption, event-based implementations of neural networks have not been able to achieve the same…
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Recurrent Neural Networks (RNNs) have become the state-of-the-art choice for extracting patterns from temporal sequences. However, current RNN models are ill-suited to process irre…
Prediction of Manipulation Actions
Cornelia Fermüller, Fang Wang, Yezhou Yang +4
Looking at a person's hands one often can tell what the person is going to do next, how his/her hands are moving and where they will be, because an actor's intentions shape his/her…