Biblio

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2017
Lukic, Y. X., Vogt C., Dürr O., & Stadelmann T. (2017).  Learning embeddings for speaker clustering based on voice equality. Machine Learning for Signal Processing (MLSP), 2017 IEEE 27th International Workshop on. 1–6.PDF icon MLSP_2017.pdf (1.34 MB)
2016
Seepold, R., Dermati C., Kostka A., Pfeil L., Lange R., Hermann M., et al. (2016).  Analyzing environmental conditions and vital signs to increase healthy living. Mobile Networks for Biometric Data Analysis.
Dürr, O., & Sick B. (2016).  Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks. Journal of biomolecular screening. 21, 998–1003.
Lukic, Y., Vogt C., Dürr O., & Stadelmann T. (2016).  Speaker Identification and Clustering using Convolution Neural Networks. IEEE International workshop on Machine Learning for Signal Processing.
2015
Dürr, O., Pauchard Y., Browarnik D., Axthelm R., & Loeser M. (2015).  Deep Learning on a Raspberry Pi for Real Time Face Recognition.. Eurographics (Posters). 11–12.
Franzini, A., Baty F., Macovei I. I., Dürr O., Droege C., Betticher D., et al. (2015).  Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced non-squamous non-small cell lung cancer patients (SAKK 19/05 trial). Clinical Cancer Research. clincanres––3135.
Franzini, A., Baty F., Macovei I. I., Dürr O., Droege C., Betticher D., et al. (2015).  Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced non-squamous non-small cell lung cancer patients (SAKK 19/05 trial). Clinical Cancer Research. clincanres––3135.
Denker, K., Hamann B., & Umlauf G. (2015).  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.PDF icon OnlineCADReconst.pdf (3.18 MB)
Caputo, M., Denker K., Franz M. O., Laube P., & Umlauf G. (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.PDF icon Caputo et al_2015_Support vector machines for classification of geometric primitives in point clouds.pdf (2.64 MB)
Danhof, M., Schneider T., Laube P., & Umlauf G. (2015).  A Virtual-Reality 3d-Laser-Scan Simulation. BW-CAR| SINCOM. 68.

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