Germain Haessig

According to our database, Germain Haessig authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers.

Gerald Ebmer, Adam Loch, Minh Nhat Vu, Roberto Mecca, Germain Haessig, Christian Hartl-Nesic, Markus Vincze, Andreas Kugi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

PDAVIS: Bio-inspired Polarization Event Camera.

Germain Haessig, Damien Joubert, Justin Haque, Moritz B. Milde, Tobi Delbruck, Viktor Gruev

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events.

Tobi Delbruck, Zuowen Wang, Haiyang Mei, Germain Haessig, Damien Joubert, Justin Haque, Yingkai Chen, Moritz B. Milde, Viktor Gruev

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems.

Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021

Bio-inspired Polarization Event Camera.

Germain Haessig, Damien Joubert, Justin Haque, Yingkai Chen, Moritz B. Milde, Tobi Delbrück, Viktor Gruev

CoRR, 2021

Event-Based high-speed low-latency fiducial marker tracking.

Adam Loch, Germain Haessig, Markus Vincze

CoRR, 2021

Online Detection of Vibration Anomalies Using Balanced Spiking Neural Networks.

Nik Dennler, Germain Haessig, Matteo Cartiglia, Giacomo Indiveri

Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021

2020

A Mixed-Signal Spatio-Temporal Signal Classifier for On-Sensor Spike Sorting.

Germain Haessig, Daniel García-Lesta, Gregor Lenz, Ryad Benosman, Piotr Dudek

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

Lessons Learned the Hard Way.

Tobi Delbrück, Ibrahim Abe M. Elfadel, Shahzad Muzaffar, Germain Haessig, Bo Wang, Amine Bermak, Rui Graca, Luis A. Camuñas-Mesa, Bathiya Senevirathna, Pamela Abshire, Bernabé Linares-Barranco, Saeed Afshar, Shih-Chii Liu, Runchun Mark Wang, Piotr Dudek, Stephen J. Carey, José M. de la Rosa, Marc Dandin, Sheung Lu, Vincent Frick, Teresa Serrano-Gotarredona, Paula López, Melika Payvand, Advait Madhavan, Eric R. Fossum, Juan Camilo Vasquez Tieck, Ian Williams, Yan Liu, Timothy G. Constandinou, Alexander Serb, Ricardo Carmona-Galán, Robert Nawrocki, Walter D. Leon-Salas

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

An error-propagation spiking neural network compatible with neuromorphic processors.

Matteo Cartiglia, Germain Haessig, Giacomo Indiveri

Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

2019

Neuromorphic networks on the SpiNNaker platform.

Germain Haessig, Francesco Galluppi, Xavier Lagorce, Ryad Benosman

Proceedings of the IEEE International Conference on Artificial Intelligence Circuits and Systems, 2019

2018

Spiking Optical Flow for Event-Based Sensors Using IBM's TrueNorth Neurosynaptic System.

Germain Haessig, Andrew Cassidy, Rodrigo Alvarez-Icaza, Ryad Benosman, Garrick Orchard

IEEE Trans. Biomed. Circuits Syst., 2018

A Sparse Coding Multi-Scale Precise-Timing Machine Learning Algorithm for Neuromorphic Event-Based Sensors.

Germain Haessig, Ryad Benosman

CoRR, 2018