Search Results for author: Gregor Lenz

Found 9 papers, 8 papers with code

Ultra-low-power Image Classification on Neuromorphic Hardware

1 code implementation28 Sep 2023 Gregor Lenz, Garrick Orchard, Sadique Sheik

We propose a temporal ANN-to-SNN conversion method, which we call Quartz, that is based on the time to first spike (TTFS).

Classification Image Classification

NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

1 code implementation10 Apr 2023 Jason Yik, Korneel Van den Berghe, Douwe den Blanken, Younes Bouhadjar, Maxime Fabre, Paul Hueber, Denis Kleyko, Noah Pacik-Nelson, Pao-Sheng Vincent Sun, Guangzhi Tang, Shenqi Wang, Biyan Zhou, Soikat Hasan Ahmed, George Vathakkattil Joseph, Benedetto Leto, Aurora Micheli, Anurag Kumar Mishra, Gregor Lenz, Tao Sun, Zergham Ahmed, Mahmoud Akl, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Petrut Bogdan, Sander Bohte, Sonia Buckley, Gert Cauwenberghs, Elisabetta Chicca, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Tobias Fischer, Jeremy Forest, Vittorio Fra, Steve Furber, P. Michael Furlong, William Gilpin, Aditya Gilra, Hector A. Gonzalez, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Yao-Hong Liu, Shih-Chii Liu, Haoyuan Ma, Rajit Manohar, Josep Maria Margarit-Taulé, Christian Mayr, Konstantinos Michmizos, Dylan Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayca Ozcelikkale, Priyadarshini Panda, Jongkil Park, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Alessandro Pierro, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Samuel Schmidgall, Catherine Schuman, Jae-sun Seo, Sadique Sheik, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Matthew Stewart, Kenneth Stewart, Terrence C. Stewart, Philipp Stratmann, Jonathan Timcheck, Nergis Tömen, Gianvito Urgese, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi

The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings.


EXODUS: Stable and Efficient Training of Spiking Neural Networks

1 code implementation20 May 2022 Felix Christian Bauer, Gregor Lenz, Saeid Haghighatshoar, Sadique Sheik

In this paper, (i) we modify SLAYER and design an algorithm called EXODUS, that accounts for the neuron reset mechanism and applies the Implicit Function Theorem (IFT) to calculate the correct gradients (equivalent to those computed by BPTT), (ii) we eliminate the need for ad-hoc scaling of gradients, thus, reducing the training complexity tremendously, (iii) we demonstrate, via computer simulations, that EXODUS is numerically stable and achieves a comparable or better performance than SLAYER especially in various tasks with SNNs that rely on temporal features.

A Framework for Event-based Computer Vision on a Mobile Device

1 code implementation13 May 2022 Gregor Lenz, Serge Picaud, Sio-Hoi Ieng

We present the first publicly available Android framework to stream data from an event camera directly to a mobile phone.

Face Detection Gesture Recognition +2

A sampling-based approach for efficient clustering in large datasets

1 code implementation CVPR 2022 Georgios Exarchakis, Omar Oubari, Gregor Lenz

We propose a simple and efficient clustering method for high-dimensional data with a large number of clusters.


Adversarial Attacks on Spiking Convolutional Neural Networks for Event-based Vision

1 code implementation6 Oct 2021 Julian Büchel, Gregor Lenz, Yalun Hu, Sadique Sheik, Martino Sorbaro

Event-based dynamic vision sensors provide very sparse output in the form of spikes, which makes them suitable for low-power applications.

Adversarial Attack Event-based vision

Training Spiking Neural Networks Using Lessons From Deep Learning

3 code implementations27 Sep 2021 Jason K. Eshraghian, Max Ward, Emre Neftci, Xinxin Wang, Gregor Lenz, Girish Dwivedi, Mohammed Bennamoun, Doo Seok Jeong, Wei D. Lu

This paper serves as a tutorial and perspective showing how to apply the lessons learnt from several decades of research in deep learning, gradient descent, backpropagation and neuroscience to biologically plausible spiking neural neural networks.

Event-based Face Detection and Tracking in the Blink of an Eye

no code implementations27 Mar 2018 Gregor Lenz, Sio-Hoi Ieng, Ryad Benosman

We will rely on a new feature that has never been used for such a task that relies on detecting eye blinks.

Face Detection Position

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