Biblio
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Author Title Type [ Year
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Deep and interpretable regression models for ordinal outcomes.
arXiv preprint. 2010.08376.
(2020). Detecting and mapping tree seedlings in UAV imagery using convolutional neural networks and field-verified data.
ISPRS Journal of Photogrammetry and Remote Sensing. 168, 156 - 169.
(2020). Integrating uncertainty in deep neural networks for MRI based stroke analysis.
Medical Image Analysis. 65, 101790.
(2020). Ordinal neural network transformation models: deep and interpretable regression models for ordinal outcomes.
arXiv e-prints. 2010.08376.
(2020).
(2020).
(2020). Single Shot MC Dropout Approximation.
ICML Workshop on Uncertainty and Robustness in Deep Learning.
(2020). Beyond ImageNet: Deep Learning in Industrial Practice.
Applied Data Science. 205-232.
(2019).
(2019). Automatic classification of non-small cell lung cancer histologic sub-types by deep learning.
VIRCHOWS ARCHIV. 108-108.
(2018). Developing deep learning applications for life science and pharma industry.
Drug research. 68, 305–310.
(2018). Learning to Cluster.
learning_to_cluster.pdf (1.82 MB)
(2018). 
Analyzing environmental conditions and vital signs to increase healthy living.
Mobile Networks for Biometric Data Analysis.
(2016). On-line CAD Reconstruction with Accumulated Means of Local Geometric Properties.
(Boissonnat, J-D., Cohen A., Gibaru O., Gout C., Lyche T., Mazure M-L., et al., Ed.).Curves and Surfaces, 8th International Conference, Paris 2014. 181-201.
OnlineCADReconst.pdf (3.18 MB)
(2015). 
Support Vector Machines for Classification of Geometric Primitives in Point Clouds.
(Boissonnat, J-D., Cohen A., Gibaru O., Gout C., Lyche T., Mazure M-L., et al., Ed.).Curves and Surfaces, 8th International Conference, Paris 2014. 80-95.
Caputo et al_2015_Support vector machines for classification of geometric primitives in point clouds.pdf (2.64 MB)
(2015). 
A Virtual-Reality 3d-Laser-Scan Simulation.
BW-CAR| SINCOM. 68.
(2015). On-line reconstruction of CAD geometry.
International Conference on 3d Vision.
OnlineReconstruction.pdf (392.38 KB)
(2013). 
3d hand gesture recognition based on sensor fusion of commodity hardware.
(Reiterer, H., & Deussen O., Ed.).Mensch und Computer.
GestureRecognition.pdf (378.26 KB)
(2012). 
3d hand gesture recognition based on sensor fusion of commodity hardware.
(Reiterer, H., & Deussen O., Ed.).Mensch und Computer.
GestureRecognition.pdf (378.26 KB)
(2012). 
3d hand gesture recognition based on sensor fusion of commodity hardware.
(Reiterer, H., & Deussen O., Ed.).Mensch und Computer.
GestureRecognition.pdf (378.26 KB)
(2012). 
A hand-held laser scanner based on multi-camera stereo-matching.
Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop.
LaserScannerStereoMatching.pdf (584.47 KB)
(2012). 
An accurate real-time multi-camera matching on the GPU for 3d reconstruction.
Journal of WSCG. 19, 9-16.
RealTimeMultiCamera.pdf (770.39 KB)
(2011). 
Real-time triangulation of point streams.
Engineering with Computers. 27, 67-80.
RTTriangulationPointStreams.pdf (1.05 MB)
(2011). 
Survey on benchmarks for a GPU based multi camera stereo matching algorithm.
Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop.
BenchmarkStereoMatching.pdf (3.63 MB)
(2011). 
Geometric properties of the adaptice Delaunay tessellation.
(Dæhlen, M., Floater M.S., Lyche T., Merrien J.-L., Morken K., & Schumaker L.L., Ed.).Mathematical Methods of Curves and Surfaces, Tondsberg 2008.
ADTProperties.pdf (335.14 KB)
(2010). 