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Germain Haessig
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2020 – today
- 2024
- [c9]Gerald Ebmer, Adam Loch, Minh Nhat Vu, Roberto Mecca, Germain Haessig, Christian Hartl-Nesic, Markus Vincze, Andreas Kugi:
Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers. WACV 2024: 8122-8131 - 2023
- [c8]Germain Haessig, Damien Joubert, Justin Haque, Moritz B. Milde, Tobi Delbruck, Viktor Gruev:
PDAVIS: Bio-inspired Polarization Event Camera. CVPR Workshops 2023: 3963-3972 - [c7]Tobi Delbruck, Zuowen Wang, Haiyang Mei, Germain Haessig, Damien Joubert, Justin Haque, Yingkai Chen, Moritz B. Milde, Viktor Gruev:
Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events. CVPR Workshops 2023: 3973-3975 - [i8]Gerald Ebmer, Adam Loch, Minh Nhat Vu, Germain Haessig, Roberto Mecca, Markus Vincze, Christian Hartl-Nesic, Andreas Kugi:
Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers. CoRR abs/2310.16618 (2023) - 2022
- [c6]Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand:
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. ISCAS 2022: 476-480 - [i7]Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand:
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. CoRR abs/2201.10409 (2022) - 2021
- [c5]Nik Dennler, Germain Haessig, Matteo Cartiglia, Giacomo Indiveri:
Online Detection of Vibration Anomalies Using Balanced Spiking Neural Networks. AICAS 2021: 1-4 - [i6]Matteo Cartiglia, Germain Haessig, Giacomo Indiveri:
An error-propagation spiking neural network compatible with neuromorphic processors. CoRR abs/2104.05241 (2021) - [i5]Nik Dennler, Germain Haessig, Matteo Cartiglia, Giacomo Indiveri:
Online Detection of Vibration Anomalies Using Balanced Spiking Neural Networks. CoRR abs/2106.00687 (2021) - [i4]Adam Loch, Germain Haessig, Markus Vincze:
Event-Based high-speed low-latency fiducial marker tracking. CoRR abs/2110.05819 (2021) - [i3]Germain Haessig, Damien Joubert, Justin Haque, Yingkai Chen, Moritz B. Milde, Tobi Delbrück, Viktor Gruev:
Bio-inspired Polarization Event Camera. CoRR abs/2112.01933 (2021) - 2020
- [c4]Matteo Cartiglia, Germain Haessig, Giacomo Indiveri:
An error-propagation spiking neural network compatible with neuromorphic processors. AICAS 2020: 84-88 - [c3]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:
Lessons Learned the Hard Way. ISCAS 2020: 1-18 - [c2]Germain Haessig, Daniel García-Lesta, Gregor Lenz, Ryad Benosman, Piotr Dudek:
A Mixed-Signal Spatio-Temporal Signal Classifier for On-Sensor Spike Sorting. ISCAS 2020: 1-5
2010 – 2019
- 2019
- [c1]Germain Haessig, Francesco Galluppi, Xavier Lagorce, Ryad Benosman:
Neuromorphic networks on the SpiNNaker platform. AICAS 2019: 86-91 - 2018
- [j1]Germain Haessig, Andrew Cassidy, Rodrigo Alvarez-Icaza, Ryad Benosman, Garrick Orchard:
Spiking Optical Flow for Event-Based Sensors Using IBM's TrueNorth Neurosynaptic System. IEEE Trans. Biomed. Circuits Syst. 12(4): 860-870 (2018) - [i2]Germain Haessig, Ryad Benosman:
A Sparse Coding Multi-Scale Precise-Timing Machine Learning Algorithm for Neuromorphic Event-Based Sensors. CoRR abs/1804.09236 (2018) - 2017
- [i1]Germain Haessig, Andrew Cassidy, Rodrigo Alvarez-Icaza, Ryad Benosman, Garrick Orchard:
Spiking Optical Flow for Event-based Sensors Using IBM's TrueNorth Neurosynaptic System. CoRR abs/1710.09820 (2017)
Coauthor Index
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last updated on 2024-05-08 21:46 CEST by the dblp team
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