Michael Pfeiffer
Michael Pfeiffer
Bosch Center for Artificial Intelligence
Verified email at de.bosch.com - Homepage
Title
Cited by
Cited by
Year
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
4572015
Training deep spiking neural networks using backpropagation
JH Lee, T Delbruck, M Pfeiffer
Frontiers in neuroscience 10, 508, 2016
3992016
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, 178, 2013
3652013
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
2702017
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
2422016
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
2342013
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, 682, 2017
2132017
Deep learning with spiking neurons: opportunities and challenges
M Pfeiffer, T Pfeil
Frontiers in neuroscience 12, 774, 2018
1632018
STDP enables spiking neurons to detect hidden causes of their inputs
B Nessler, M Pfeiffer, W Maass
Advances in neural information processing systems 22, 1357-1365, 2009
1102009
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, 222, 2015
842015
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
63*2015
DVS benchmark datasets for object tracking, action recognition, and object recognition
Y Hu, H Liu, M Pfeiffer, T Delbruck
Frontiers in neuroscience 10, 405, 2016
572016
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
512016
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
502017
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, 429, 2015
482015
Reinforcement learning of strategies for Settlers of Catan
M Pfeiffer
Proceedings of the International Conference on Computer Games: Artificial …, 2004
482004
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
442014
Semantic segmentation of colon glands with deep convolutional neural networks and total variation segmentation
P Kainz, M Pfeiffer, M Urschler
arXiv preprint arXiv:1511.06919, 2015
412015
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
382016
Prediction of manipulation actions
C Fermüller, F Wang, Y Yang, K Zampogiannis, Y Zhang, F Barranco, ...
International Journal of Computer Vision 126 (2-4), 358-374, 2018
362018
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