Daniel Keysers
- Research Area(s)
- Human-Computer Interaction and Visualization
- Mobile Systems
Co-Authors
Google Publications
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Multi-Language Online Handwriting Recognition
Daniel Keysers, Thomas Deselaers, Henry A. Rowley, Li-Lun Wang, Victor Carbune
IEEE Transactions on Pattern Analysis and Machine Intelligence (2016)
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GyroPen: Gyroscopes for Pen-input with Mobile Phones
Thomas Deselaers, Daniel Keysers, Jan Hosang, Henry Rowley
IEEE Transactions on Human-Machine Systems, vol. 45 (2015), pp. 263-271
Previous Publications
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Features for image retrieval: an experimental comparison
Thomas Deselaers, Daniel Keysers, Hermann Ney
Information Retrieval, vol. 11 (2008), pp. 77-107
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Deformation models for image recognition
Daniel Keysers, Thomas Deselaers, Christian Gollan, Hermann Ney
Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 29 (2007), pp. 1422-1435
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Discriminative Training for Object Recognition using Image Patches
Thomas Deselaers, Daniel Keysers, Hermann Ney
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2005)
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Improving a Discriminative Approach to Object Recognition using Image Patches.
Thomas Deselaers, Daniel Keysers, Hermann Ney
Pattern Recognition (DAGM) (2005)
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Adaptation in Statistical Pattern Recognition Using Tangent Vectors
Daniel Keysers, Wolfgang Macherey, Hermann Ney, Joerg Dahmen
IEEE Trans. Pattern Analysis Machine Intelligence, vol. 26 (2004), pp. 269-274
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Elastic image matching is NP-complete
Daniel Keysers, Walter Unger
Pattern Recognition Letters, vol. 24 (2003), pp. 445-453
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Maximum Entropy and Gaussian Models for Image Object Recognition
Daniel Keysers, Franz Josef Och, Hermann Ney
DAGM-Symposium (2002), pp. 498-506
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Improving Automatic Speech Recognition Using Tangent Distance
Wolfgang Macherey, Daniel Keysers, Joerg Dahmen, Hermann Ney
European Conference on Speech Communication and Technology (2001)
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Learning of Variability for Invariant Statistical Pattern Recognition
Daniel Keysers, Wolfgang Macherey, Joerg Dahmen, Hermann Ney
European Conference on Machine Learning (ECML) (2001), pp. 263-275




