Hannes Schulz
Hannes Schulz
Microsoft Research, Montreal
Verified email at microsoft.com
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
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
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
Towards deep conversational recommendations
R Li, S Kahou, H Schulz, V Michalski, L Charlin, C Pal
arXiv preprint arXiv:1812.07617, 2018
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 van 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
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), vzj2012. 0019, 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
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
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
Deep learning
H Schulz, S Behnke
KI-Künstliche Intelligenz 26 (4), 357-363, 2012
Real time interaction with mobile robots using hand gestures
K Konda, H Schulz, A Königs, D Schulz
2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2012
Utilizing the structure of field lines for efficient soccer robot localization
H Schulz, S Behnke
Advanced Robotics 26 (14), 1603-1621, 2012
Recurrent convolutional neural networks for object-class segmentation of RGB-D video
MS Pavel, H Schulz, S Behnke
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
Natural language generation in dialogue using lexicalized and delexicalized data
S Sharma, J He, K Suleman, H Schulz, P Bachman
arXiv preprint arXiv:1606.03632, 2016
The system can't perform the operation now. Try again later.
Articles 1–20