Dr.-Ing. Christian Rieß

Scopus Author ID: 23393831200



Organisation


Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen)
Lehrstuhl für Informatik 5 (Mustererkennung)


Awards / Honours


2017 : Best Paper Award



Project lead


DISPARITY: Digital, Semantic and Physical Analysis of Media Integrity
Prof. Dr.-Ing. Andreas Maier; Dr.-Ing. Christian Riess
(24/05/2016 - 23/05/2017)

Bildforensik: Analyse der digitalen Integrität von Bildern und Videos
Dr.-Ing. Christian Riess; Prof. Dr. Marc Stamminger
(01/05/2016)


Project member


RoboCup Robot Soccer
Prof. Dr. Björn Eskofier
(01/01/2008)


Publications (Download BibTeX)

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Felsner, L., Hu, S., Maier, A., Bopp, J., Ludwig, V., Anton, G., & Riess, C. (2019). A 3-D Projection Model for X-ray Dark-field Imaging. Scientific Reports, 9.
Maier, A., Syben, C., Lasser, T., & Riess, C. (2019). A gentle introduction to deep learning in medical image processing [Eine sanfte Einführung in Tiefes Lernen in der Medizinischen Bildverarbeitung]. Zeitschrift für Medizinische Physik, 29(2), 86-101. https://dx.doi.org/10.1016/j.zemedi.2018.12.003
Deitsch, S., Christlein, V., Berger, S., Buerhop-Lutz, C., Maier, A., Gallwitz, F., & Riess, C. (2019). Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images. Solar Energy, 185, 455-468. https://dx.doi.org/10.1016/j.solener.2019.02.067
Deitsch, S., Christlein, V., Berger, S., Buerhop-Lutz, C., Maier, A., Gallwitz, F., & Rieß, C. (2019). Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images. Solar Energy, 185, 455-468. https://dx.doi.org/10.1016/j.solener.2019.02.067
Matern, F., Riess, C., & Stamminger, M. (2019). Exploiting Visual Artifacts to Expose Deepfakes and Face Manipulations. In IEEE Workshop on Applications in Computer Vision (pp. 83-92). Waikoloa Village, HI, US: IEEE.
Roessler, A., Cozzolino, D., Verdoliva, L., Rieß, C., Thies, J., & Niessner, M. (2019). FaceForensics++: Learning to Detect Manipulated Facial Images.
Davari, A., Özkan, H.C., Maier, A., & Rieß, C. (2019). Fast and Efficient Limited Data Hyperspectral Remote Sensing Image Classification via GMM-Based Synthetic Samples. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(7), 2107-2120. https://dx.doi.org/10.1109 / JSTARS.2019.2916495
Mullan, P., Rieß, C., & Freiling, F. (2019). Forensic Source Identification using JPEG Image Headers: The Case of Smartphones. In Digital Investigation. Oslo, NO.
Mullan, P., Riess, C., & Freiling, F. (2019). Forensic source identification using JPEG image headers: The case of smartphones. Digital Investigation, 28, S68-S76. https://dx.doi.org/10.1016/j.diin.2019.01.016
Lorch, B., & Riess, C. (2019). Image Forensics from Chroma Subsampling of High-Quality JPEG Images. In Proceedings of the ACM Workshop on Information Hiding and Multimedia Security. Paris, FR.

Last updated on 2019-22-01 at 17:51