Deep-Learning | [1,4] |
Classification | [1,2,3,4,5] |
Discriminative Models | [1,2,3,5]
|
Generative Models | [4] |
Temporal Data | [1,4] |
Categorical Data | [2,3] |
Outlier Detection | [4] |
Benchmarking | [1,4,5] |
Open-Set Problem | [2] |
Statistical Modeling | [4] |
Metric Learning and Manifolds | [4] |
Classification | [6,7] |
Discriminative Models | [7]
|
Regresion | [6] |
Temporal Data | [6,7] |
Digital Filters | [6,7] |
Wavelet Denoising | [7] |
[1] Compression Forensics on High-Quality Video
[2] Towards Open-Set Forensic Source Grouping on JPEG Header Information
[3] Forensic Source Identification using JPEG Image Headers: The Case of Smartphones
[4] Residual-based forensic comparison of Video Sequences
[5] Camera Fingerprinting Authentication Revisited (Distinguished Paper Award)
[6] Detection of Fetal Kicks using Body-worn Accelerometers during Pregnancy
[7] Unobtrusive Heart Rate Estimation during Physical Excercise using Photoplethsmographic and Acceleration Data
Reseache & Development |
|
Document Identification | |
Image Retrieval | |
Consistency Checks | |
Statistical Modeling | |
Examining Large Datasets | |
From Prototyping ... | |
... to Productive Code |
Image Segmentation | |
Optical Character Recognition (OCR) |
|
SVMs | |
Data Recording | |
Data Preparation | |
Prototyping |
Title | Venue |
---|---|
Digital Cues of Multimedia Forensics | Doctoral Defense, FAU, 2020 |
Do modern smartphones automatically forge images? | Lightning-Talks, FAU, 2020 |
Source-Identication of Images with help of JPEG Header files | Cast-Workshop, Fraunhofer-Institut Darmstadt, 2019 |
The digital Fingerprint of a Camera Sensor | Lange Nacht der Wissenschaft, FAU, 2019 |
How do machines actually learn? | Philosophical-Seminar, FAU, 2017 |
Bildkompression -- Oder wie das Kamel durch ein Nadelöhr kommt | E-Werk Erlangen, 2014, available online (in German) |