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Michael Pfeiffer

Bosch Center for Artificial Intelligence, Renningen, Germany

Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra


Jun 01, 2021
Kanil Patel, William Beluch, Kilian Rambach, Adriana-Eliza Cozma, Michael Pfeiffer, Bin Yang

* IEEE Radar Conference 2021 
* 6 pages 

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Bosch Deep Learning Hardware Benchmark


Aug 24, 2020
Armin Runge, Thomas Wenzel, Dimitrios Bariamis, Benedikt Sebastian Staffler, Lucas Rego Drumond, Michael Pfeiffer

* Presented in MLBench: Workshop on Benchmarking Machine Learning Workloads (https://sites.google.com/g.harvard.edu/mlbench/home

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Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning


Jun 23, 2020
Kanil Patel, William Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang


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On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration


Dec 16, 2019
Kanil Patel, William Beluch, Dan Zhang, Michael Pfeiffer, Bin Yang


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Robust Anomaly Detection in Images using Adversarial Autoencoders


Jan 18, 2019
Laura Beggel, Michael Pfeiffer, Bernd Bischl


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Data-driven Summarization of Scientific Articles


Apr 24, 2018
Nikola I. Nikolov, Michael Pfeiffer, Richard H. R. Hahnloser

* 8 pages, 3 figures. 7th International Workshop on Mining Scientific Publications, LREC 2018 

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Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation


Oct 10, 2017
Philipp Kainz, Michael Pfeiffer, Martin Urschler

* An extended version of this work has been published in PeerJ (https://doi.org/10.7717/peerj.3874), so please cite our journal version instead of this preprint 

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Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks


Dec 13, 2016
Bodo Rueckauer, Iulia-Alexandra Lungu, Yuhuang Hu, Michael Pfeiffer

* 9 pages, 2 figures, presented at the workshop "Computing with Spikes" at NIPS 2016, Barcelona, Spain 

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Deep counter networks for asynchronous event-based processing


Nov 02, 2016
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer


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Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences


Oct 29, 2016
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu

* Selected for an oral presentation at NIPS, 2016 

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Prediction of Manipulation Actions


Oct 03, 2016
Cornelia Fermüller, Fang Wang, Yezhou Yang, Konstantinos Zampogiannis, Yi Zhang, Francisco Barranco, Michael Pfeiffer

* 15 pages, 12 figures, 6 tables 

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Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest


Sep 01, 2016
Korsuk Sirinukunwattana, Josien P. W. Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J. Matuszewski, Elia Bruni, Urko Sanchez, Anton Böhm, Olaf Ronneberger, Bassem Ben Cheikh, Daniel Racoceanu, Philipp Kainz, Michael Pfeiffer, Martin Urschler, David R. J. Snead, Nasir M. Rajpoot


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Training Deep Spiking Neural Networks using Backpropagation


Aug 31, 2016
Jun Haeng Lee, Tobi Delbruck, Michael Pfeiffer


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Precise deep neural network computation on imprecise low-power analog hardware


Jun 23, 2016
Jonathan Binas, Daniel Neil, Giacomo Indiveri, Shih-Chii Liu, Michael Pfeiffer


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Spiking Analog VLSI Neuron Assemblies as Constraint Satisfaction Problem Solvers


Apr 06, 2016
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer

* Accepted at ISCAS 2016 

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