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Bodo Rueckauer
Title
Cited by
Cited by
Year
Conversion of continuous-valued deep networks to efficient event-driven networks for image classification
B Rueckauer, IA Lungu, Y Hu, M Pfeiffer, SC Liu
Frontiers in neuroscience 11, 294078, 2017
9472017
Conversion of analog to spiking neural networks using sparse temporal coding
B Rueckauer, SC Liu
2018 IEEE international symposium on circuits and systems (ISCAS), 1-5, 2018
1992018
Evaluation of event-based algorithms for optical flow with ground-truth from inertial measurement sensor
B Rueckauer, T Delbruck
Frontiers in neuroscience 10, 173156, 2016
1382016
Theory and tools for the conversion of analog to spiking convolutional neural networks
B Rueckauer, IA Lungu, Y Hu, M Pfeiffer
arXiv preprint arXiv:1612.04052, 2016
1372016
Event-driven sensing for efficient perception: Vision and audition algorithms
SC Liu, B Rueckauer, E Ceolini, A Huber, T Delbruck
IEEE Signal Processing Magazine 36 (6), 29-37, 2019
722019
NxTF: An API and compiler for deep spiking neural networks on Intel Loihi
B Rueckauer, C Bybee, R Goettsche, Y Singh, J Mishra, A Wild
ACM Journal on Emerging Technologies in Computing Systems (JETC) 18 (3), 1-22, 2022
452022
Optimization of neuroprosthetic vision via end-to-end deep reinforcement learning
B Küçükoğlu, B Rueckauer, N Ahmad, JR van Steveninck, U Güçlü, ...
International Journal of Neural Systems 32 (11), 2250052, 2022
202022
Closing the accuracy gap in an event-based visual recognition task
B Rückauer, N Känzig, SC Liu, T Delbruck, Y Sandamirskaya
arXiv preprint arXiv:1906.08859, 2019
202019
Reducing latency in a converted spiking video segmentation network
Q Cheni, B Rueckauer, L Li, T Delbruck, SC Liu
2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2021
132021
Conversion of analog to spiking neural networks using sparse temporal coding, 2018 IEEE Int. Symp. Circuits and Systems (ISCAS)
B Rueckauer, SC Liu
IEEE, 2018
122018
Temporal Pattern Coding in Deep Spiking Neural Networks
B Rueckauer, SC Liu
International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
112021
New features of receptive fields in mouse retina through spike-triggered covariance
J Ahn, B Rueckauer, Y Yoo, YS Goo
Experimental neurobiology 29 (1), 38, 2020
92020
An in-silico framework for modeling optimal control of neural systems
B Rueckauer, M van Gerven
Frontiers in Neuroscience 17, 1141884, 2023
42023
Biologically plausible phosphene simulation for the differentiable optimization of visual cortical prostheses
M Van Der Grinten, J de Ruyter van Steveninck, A Lozano, L Pijnacker, ...
bioRxiv, 2022.12. 23.521749, 2022
42022
Real-time edge neuromorphic tasting from chemical microsensor arrays
N LeBow, B Rueckauer, P Sun, M Rovira, C Jiménez-Jorquera, SC Liu, ...
Frontiers in Neuroscience 15, 771480, 2021
42021
Contraction of dynamically masked deep neural networks for efficient video processing
B Rueckauer, SC Liu
IEEE Transactions on Circuits and Systems for Video Technology 32 (2), 621-633, 2021
42021
Method and apparatus with neural network layer contraction
SC Liu, B Rueckauer, T Delbruck
US Patent App. 16/739,543, 2020
42020
LiteEdge: Lightweight Semantic Edge Detection Network
H Wang, H Mohamed, Z Wang, B Rueckauer, SC Liu
International Conference on Computer Vision (ICCV), 1-10, 2021
32021
Towards biologically plausible phosphene simulation for the differentiable optimization of visual cortical prostheses
M van der Grinten, JR van Steveninck, A Lozano, L Pijnacker, ...
Elife 13, e85812, 2024
22024
Linear approximation of deep neural networks for efficient inference on video data
B Rueckauer, SC Liu
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
22019
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Articles 1–20