Michael Pfeiffer
Michael Pfeiffer
Bosch Center for Artificial Intelligence
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Fast-Classifying, High-Accuracy Spiking Deep Networks Through Weight and Threshold Balancing
PU Diehl, D Neil, J Binas, M Cook, SC Liu, M Pfeiffer
International Joint Conference on Neural Networks (IJCNN), 2015
Training deep spiking neural networks using backpropagation
JH Lee, T Delbruck, M Pfeiffer
Frontiers in neuroscience 10, 228000, 2016
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
Gland segmentation in colon histology images: The glas challenge contest
K Sirinukunwattana, JPW Pluim, H Chen, X Qi, PA Heng, YB Guo, ...
Medical image analysis 35, 489-502, 2017
Deep learning with spiking neurons: Opportunities and challenges
M Pfeiffer, T Pfeil
Frontiers in neuroscience 12, 409662, 2018
Phased LSTM: Accelerating recurrent network training for long or event-based sequences
D Neil, M Pfeiffer, SC Liu
Advances in Neural Information Processing Systems, 3882-3890, 2016
Real-time classification and sensor fusion with a spiking deep belief network
P O'Connor, D Neil, SC Liu, T Delbruck, M Pfeiffer
Frontiers in neuroscience 7, 58710, 2013
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity
B Nessler, M Pfeiffer, L Büsing, W Maass
PLoS Computational Biology 9 (4), e1003037, 2013
DVS benchmark datasets for object tracking, action recognition, and object recognition
Y Hu, H Liu, M Pfeiffer, T Delbruck
Frontiers in neuroscience 10, 210251, 2016
STDP enables spiking neurons to detect hidden causes of their inputs
B Nessler, M Pfeiffer, W Maass
Advances in neural information processing systems 22, 2009
Robust anomaly detection in images using adversarial autoencoders
L Beggel, M Pfeiffer, B Bischl
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020
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
Robustness of spiking deep belief networks to noise and reduced bit precision of neuro-inspired hardware platforms
E Stromatias, D Neil, M Pfeiffer, F Galluppi, SB Furber, SC Liu
Frontiers in neuroscience 9, 141542, 2015
Deep learning-based object classification on automotive radar spectra
K Patel, K Rambach, T Visentin, D Rusev, M Pfeiffer, B Yang
2019 IEEE Radar Conference (RadarConf), 1-6, 2019
Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization
P Kainz, M Pfeiffer, M Urschler
PeerJ 5, e3874, 2017
Efficient processing of spatio-temporal data streams with spiking neural networks
A Kugele, T Pfeil, M Pfeiffer, E Chicca
Frontiers in neuroscience 14, 512192, 2020
Scalable Energy-Efficient, Low-Latency Implementations of Spiking Deep Belief Networks on SpiNNaker
E Stromatias, D Neil, M Pfeiffer, F Galluppi, S Furber, SC Liu
IEEE International Joint Conference on Neural Networks (IJCNN), 2015
Learning to be efficient: Algorithms for training low-latency, low-compute deep spiking neural networks
D Neil, M Pfeiffer, SC Liu
Proceedings of the 31st annual ACM symposium on applied computing, 293-298, 2016
Real-time gesture interface based on event-driven processing from stereo silicon retinas
JH Lee, T Delbruck, M Pfeiffer, PKJ Park, CW Shin, H Ryu, BC Kang
IEEE transactions on neural networks and learning systems 25 (12), 2250-2263, 2014
A framework for plasticity implementation on the SpiNNaker neural architecture
F Galluppi, X Lagorce, E Stromatias, M Pfeiffer, LA Plana, SB Furber, ...
Frontiers in neuroscience 8, 107917, 2015
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