User profiles for Michael Pfeiffer

Michael Pfeiffer

Bosch Center for Artificial Intelligence
Verified email at de.bosch.com
Cited by 8068

[HTML][HTML] Deep learning with spiking neurons: Opportunities and challenges

M Pfeiffer, T Pfeil - Frontiers in neuroscience, 2018 - frontiersin.org
Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …

[HTML][HTML] Conversion of continuous-valued deep networks to efficient event-driven networks for image classification

B Rueckauer, IA Lungu, Y Hu, M Pfeiffer… - Frontiers in …, 2017 - frontiersin.org
Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference
because the neurons in the networks are sparsely activated and computations are event-driven. …

Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing

…, J Binas, M Cook, SC Liu, M Pfeiffer - … joint conference on …, 2015 - ieeexplore.ieee.org
Deep neural networks such as Convolutional Networks (ConvNets) and Deep Belief Networks
(DBNs) represent the state-of-the-art for many machine learning and computer vision …

[HTML][HTML] Training deep spiking neural networks using backpropagation

JH Lee, T Delbruck, M Pfeiffer - Frontiers in neuroscience, 2016 - frontiersin.org
Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy
efficiency of deep neural networks through data-driven event-based computation. However…

STDP enables spiking neurons to detect hidden causes of their inputs

B Nessler, M Pfeiffer, W Maass - Advances in neural …, 2009 - proceedings.neurips.cc
The principles by which spiking neurons contribute to the astounding computational power
of generic cortical microcircuits, and how spike-timing-dependent plasticity (STDP) of …

Gland segmentation in colon histology images: The glas challenge contest

…, BB Cheikh, D Racoceanu, P Kainz, M Pfeiffer… - Medical image …, 2017 - Elsevier
Colorectal adenocarcinoma originating in intestinal glandular structures is the most common
form of colon cancer. In clinical practice, the morphology of intestinal glands, including …

[HTML][HTML] Real-time classification and sensor fusion with a spiking deep belief network

…, D Neil, SC Liu, T Delbruck, M Pfeiffer - Frontiers in …, 2013 - frontiersin.org
Deep Belief Networks (DBNs) have recently shown impressive performance on a broad
range of classification problems. Their generative properties allow better understanding of the …

Phased lstm: Accelerating recurrent network training for long or event-based sequences

D Neil, M Pfeiffer, SC Liu - Advances in neural information …, 2016 - proceedings.neurips.cc
Recurrent Neural Networks (RNNs) have become the state-of-the-art choice for extracting
patterns from temporal sequences. Current RNN models are ill suited to process irregularly …

Clinical acceptance and accuracy assessment of spinal implants guided with SpineAssist surgical robot: retrospective study

DP Devito, L Kaplan, R Dietl, M Pfeiffer, D Horne… - Spine, 2010 - journals.lww.com
Study Design. Retrospective, multicenter study of robotically-guided spinal implant insertions.
Clinical acceptance of the implants was assessed by intraoperative radiograph, and when …

[HTML][HTML] Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity

B Nessler, M Pfeiffer, L Buesing… - PLoS computational …, 2013 - journals.plos.org
The principles by which networks of neurons compute, and how spike-timing dependent
plasticity (STDP) of synaptic weights generates and maintains their computational function, are …