2.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- ETH ZurichCH61 papers
- University of ZurichCH59 papers
- SIB Swiss Institute of BioinformaticsCH13 papers
- Forschungszentrum JülichDE4 papers
- Italian Institute of TechnologyIT4 papers
- Universidad de SevillaES4 papers
- Intel (United States)US3 papers
- Swiss Federal Institute of Aquatic Science and TechnologyCH3 papers
- University of BernCH3 papers
- Accenture (United States)US2 papers
- Bielefeld UniversityDE2 papers
- California Institute of TechnologyUS2 papers
13 papers · 1 filter
Adaptive Extreme Edge Computing for Wearable Devices
Erika Covi, Elisa Donati, Hadi Heidari +4
Wearable devices are a fast-growing technology with impact on personal healthcare for both society and economy. Due to the widespread of sensors in pervasive and distributed networ…
An electronic neuromorphic system for real-time detection of High Frequency Oscillations (HFOs) in intracranial EEG
Mohammadali Sharifshazileh, Karla Burelo, Johannes Sarnthein +1
In this work, we present a neuromorphic system that combines for the first time a neural recording headstage with a signal-to-spike conversion circuit and a multi-core spiking neur…
Closed-loop spiking control on a neuromorphic processor implemented on the iCub
Jingyue Zhao, Nicoletta Risi, Marco Monforte +3
Despite neuromorphic engineering promises the deployment of low latency, adaptive and low power systems that can lead to the design of truly autonomous artificial agents, the devel…
Learning-based Defect Recognition for Quasi-Periodic Microscope Images
Nik Dennler, Antonio Foncubierta-Rodriguez, Titus Neupert +1
Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect a…
Visual Pattern Recognition with on On-chip Learning: towards a Fully Neuromorphic Approach
Sandro Baumgartner, Alpha Renner, Raphaela Kreiser +3
We present a spiking neural network (SNN) for visual pattern recognition with on-chip learning on neuromorphichardware. We show how this network can learn simple visual patterns co…
Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence
Arianna Rubino, Can Livanelioglu, Ning Qiao +2
Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal n…
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
Mostafa Rahimi Azghadi, Corey Lammie, Jason K. Eshraghian +4
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorit…
Second-order Phase Transition in Phytoplankton Trait Dynamics
Jenny Held, Tom Lorimer, Francesco Pomati +2
Key traits of unicellular species, like cell size, often follow scale-free or self-similar distributions, hinting at the possibility of an underlying critical process. However, lin…
Redesigning SLAM for Arbitrary Multi-Camera Systems
Juichung Kuo, Manasi Muglikar, Zichao Zhang +1
Adding more cameras to SLAM systems improves robustness and accuracy but complicates the design of the visual front-end significantly. Thus, most systems in the literature are tail…
Learning to Exploit Multiple Vision Modalities by Using Grafted Networks
Yuhuang Hu, Tobi Delbruck, Shih-Chii Liu
Novel vision sensors such as thermal, hyperspectral, polarization, and event cameras provide information that is not available from conventional intensity cameras. An obstacle to u…
Learning Depth With Very Sparse Supervision
Antonio Loquercio, Alexey Dosovitskiy, Davide Scaramuzza
Motivated by the astonishing capabilities of natural intelligent agents and inspired by theories from psychology, this paper explores the idea that perception gets coupled to 3D pr…
Recurrent Neural Network Control of a Hybrid Dynamic Transfemoral Prosthesis with EdgeDRNN Accelerator
Chang Gao, Rachel Gehlhar, Aaron D. Ames +2
Lower leg prostheses could improve the life quality of amputees by increasing comfort and reducing energy to locomote, but currently control methods are limited in modulating behav…
Learning the Ising Model with Generative Neural Networks
Francesco D'Angelo, Lucas Böttcher
Recent advances in deep learning and neural networks have led to an increased interest in the application of generative models in statistical and condensed matter physics. In parti…