Hannes Schulz
Hannes Schulz
Microsoft Research, Montreal
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Cited by
Cited by
RGB-D object recognition and pose estimation based on pre-trained convolutional neural network features
M Schwarz, H Schulz, S Behnke
2015 IEEE international conference on robotics and automation (ICRA), 1329-1335, 2015
Ropinirole is effective in the treatment of restless legs syndrome. TREAT RLS 2: a 12‐week, double‐blind, randomized, parallel‐group, placebo‐controlled study
AS Walters, WG Ondo, T Dreykluft, R Grunstein, D Lee, K Sethi, ...
Movement Disorders 19 (12), 1414-1423, 2004
Frames: a corpus for adding memory to goal-oriented dialogue systems
LE Asri, H Schulz, S Sharma, J Zumer, J Harris, E Fine, R Mehrotra, ...
arXiv preprint arXiv:1704.00057, 2017
Towards deep conversational recommendations
R Li, S Ebrahimi Kahou, H Schulz, V Michalski, L Charlin, C Pal
Advances in neural information processing systems 31, 2018
Relevance of unsupervised metrics in task-oriented dialogue for evaluating natural language generation
S Sharma, LE Asri, H Schulz, J Zumer
arXiv preprint arXiv:1706.09799, 2017
Policy networks with two-stage training for dialogue systems
M Fatemi, LE Asri, H Schulz, J He, K Suleman
arXiv preprint arXiv:1606.03152, 2016
Layla El Asri, Hannes Schulz, and Jeremie Zumer. 2017
S Sharma
Relevance of unsupervised metrics in task-oriented dialogue for evaluating …, 2017
Dense real-time mapping of object-class semantics from RGB-D video
J Stückler, B Waldvogel, H Schulz, S Behnke
Journal of real-time image processing 10 (4), 599-609, 2015
Accelerating large-scale convolutional neural networks with parallel graphics multiprocessors
D Scherer, H Schulz, S Behnke
International conference on Artificial neural networks, 82-91, 2010
Fast semantic segmentation of RGB-D scenes with GPU-accelerated deep neural networks
N Höft, H Schulz, S Behnke
Joint German/Austrian Conference on Artificial Intelligence (Künstliche …, 2014
Plant root system analysis from MRI images
H Schulz, JA Postma, D Dusschoten, H Scharr, S Behnke
Computer Vision, Imaging and Computer Graphics. Theory and Application, 411-425, 2013
Learning Object-Class Segmentation with Convolutional Neural Networks.
H Schulz, S Behnke
ESANN, 151-156, 2012
Deep learning
H Schulz, S Behnke
KI-Künstliche Intelligenz 26 (4), 357-363, 2012
The eighth dialog system technology challenge
S Kim, M Galley, C Gunasekara, S Lee, A Atkinson, B Peng, H Schulz, ...
arXiv preprint arXiv:1911.06394, 2019
In situ root system architecture extraction from magnetic resonance imaging for water uptake modeling
L Stingaciu, H Schulz, A Pohlmeier, S Behnke, H Zilken, M Javaux, ...
Vadose zone journal 12 (1), 1-9, 2013
Investigating convergence of restricted boltzmann machine learning
H Schulz, A Müller, S Behnke
NIPS 2010 Workshop on Deep Learning and Unsupervised Feature Learning 1 (2), 6.1, 2010
Combining semantic and geometric features for object class segmentation of indoor scenes
F Husain, H Schulz, B Dellen, C Torras, S Behnke
IEEE Robotics and Automation Letters 2 (1), 49-55, 2016
Tell, draw, and repeat: Generating and modifying images based on continual linguistic instruction
A El-Nouby, S Sharma, H Schulz, D Hjelm, LE Asri, SE Kahou, Y Bengio, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Real time interaction with mobile robots using hand gestures
KR Konda, A Königs, H Schulz, D Schulz
Proceedings of the seventh annual ACM/IEEE international conference on Human …, 2012
The KnowRef coreference corpus: Removing gender and number cues for difficult pronominal anaphora resolution
A Emami, P Trichelair, A Trischler, K Suleman, H Schulz, JCK Cheung
arXiv preprint arXiv:1811.01747, 2018
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