564 citations · 1.3k across the 25 of their papers we have counts for
32 papers
LORD: Leveraging Open-Set Recognition with Unknown Data
Tobias Koch, Christian Riess, Thomas Köhler
Handling entirely unknown data is a challenge for any deployed classifier. Classification models are typically trained on a static pre-defined dataset and are kept in the dark for…
Point to the Hidden: Exposing Speech Audio Splicing via Signal Pointer Nets
Denise Moussa, Germans Hirsch, Sebastian Wankerl +1
Verifying the integrity of voice recording evidence for criminal investigations is an integral part of an audio forensic analyst's work. Here, one focus is on detecting deletion or…
Benchmarking Probabilistic Deep Learning Methods for License Plate Recognition
Franziska Schirrmacher, Benedikt Lorch, Anatol Maier +1
Learning-based algorithms for automated license plate recognition implicitly assume that the training and test data are well aligned. However, this may not be the case under extrem…
Synthesizing Annotated Image and Video Data Using a Rendering-Based Pipeline for Improved License Plate Recognition
Andreas Spruck, Maximilane Gruber, Anatol Maier +4
An insufficient number of training samples is a common problem in neural network applications. While data augmentation methods require at least a minimum number of samples, we prop…
3D Rendering Framework for Data Augmentation in Optical Character Recognition
Andreas Spruck, Maximiliane Hawesch, Anatol Maier +3
In this paper, we propose a data augmentation framework for Optical Character Recognition (OCR). The proposed framework is able to synthesize new viewing angles and illumination sc…
Forensic License Plate Recognition with Compression-Informed Transformers
Denise Moussa, Anatol Maier, Andreas Spruck +2
Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered f…
Towards Unconstrained Audio Splicing Detection and Localization with Neural Networks
Denise Moussa, Germans Hirsch, Christian Riess
Freely available and easy-to-use audio editing tools make it straightforward to perform audio splicing. Convincing forgeries can be created by combining various speech samples from…
Deep Metric Color Embeddings for Splicing Localization in Severely Degraded Images
Benjamin Hadwiger, Christian Riess
One common task in image forensics is to detect spliced images, where multiple source images are composed to one output image. Most of the currently best performing splicing detect…
Exploring the Open World Using Incremental Extreme Value Machines
Tobias Koch, Felix Liebezeit, Christian Riess +2
Dynamic environments require adaptive applications. One particular machine learning problem in dynamic environments is open world recognition. It characterizes a continuously chang…
Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification
Mohammad Joshaghani, Amirabbas Davari, Faezeh Nejati Hatamian +2
Employing deep neural networks for Hyperspectral remote sensing (HSRS) image classification is a challenging task. HSRS images have high dimensionality and a large number of channe…
Compliance Challenges in Forensic Image Analysis Under the Artificial Intelligence Act
Benedikt Lorch, Nicole Scheler, Christian Riess
In many applications of forensic image analysis, state-of-the-art results are nowadays achieved with machine learning methods. However, concerns about their reliability and opaquen…
Deep learning architectural designs for super-resolution of noisy images
Angel Villar-Corrales, Franziska Schirrmacher, Christian Riess
Recent advances in deep learning have led to significant improvements in single image super-resolution (SR) research. However, due to the amplification of noise during the upsampli…
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
Rosanna Dietrich-Sussner, Amirabbas Davari, Thorsten Seehaus +4
Supervised machine learning requires a large amount of labeled data to achieve proper test results. However, generating accurately labeled segmentation maps on remote sensing image…
The Forchheim Image Database for Camera Identification in the Wild
Benjamin Hadwiger, Christian Riess
Image provenance can represent crucial knowledge in criminal investigation and journalistic fact checking. In the last two decades, numerous algorithms have been proposed for obtai…
Reconstruction of Voxels with Position- and Angle-Dependent Weightings
Lina Felsner, Tobias Würfl, Christopher Syben +4
The reconstruction problem of voxels with individual weightings can be modeled a position- and angle- dependent function in the forward-projection. This changes the system matrix a…
Toward Reliable Models for Authenticating Multimedia Content: Detecting Resampling Artifacts With Bayesian Neural Networks
Anatol Maier, Benedikt Lorch, Christian Riess
In multimedia forensics, learning-based methods provide state-of-the-art performance in determining origin and authenticity of images and videos. However, most existing methods are…
Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing
Prashant Chaudhari, Franziska Schirrmacher, Andreas Maier +2
High dynamic range (HDR) imaging combines multiple images with different exposure times into a single high-quality image. The image signal processing pipeline (ISP) is a core compo…
FaceForensics++: Learning to Detect Manipulated Facial Images
Andreas Rössler, Davide Cozzolino, Luisa Verdoliva +3
The rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. At best, this l…
ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detection
Davide Cozzolino, Justus Thies, Andreas Rössler +3
Distinguishing manipulated from real images is becoming increasingly difficult as new sophisticated image forgery approaches come out by the day. Naive classification approaches ba…
A 3-D Projection Model for X-ray Dark-field Imaging
Shiyang Hu, Lina Felsner, Andreas Maier +3
Talbot-Lau X-ray phase-contrast imaging is a novel imaging modality, which provides not only an X-ray absorption image, but also additionally a differential phase image and a dark-…
A Gentle Introduction to Deep Learning in Medical Image Processing
Andreas Maier, Christopher Syben, Tobias Lasser +1
This paper tries to give a gentle introduction to deep learning in medical image processing, proceeding from theoretical foundations to applications. We first discuss general reaso…
Toward Bridging the Simulated-to-Real Gap: Benchmarking Super-Resolution on Real Data
Thomas Köhler, Michel Bätz, Farzad Naderi +3
Capturing ground truth data to benchmark super-resolution (SR) is challenging. Therefore, current quantitative studies are mainly evaluated on simulated data artificially sampled f…
Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images
Sergiu Deitsch, Vincent Christlein, Stephan Berger +4
Electroluminescence (EL) imaging is a useful modality for the inspection of photovoltaic (PV) modules. EL images provide high spatial resolution, which makes it possible to detect…
Segmentation of Photovoltaic Module Cells in Uncalibrated Electroluminescence Images
Sergiu Deitsch, Claudia Buerhop-Lutz, Evgenii Sovetkin +4
High resolution electroluminescence (EL) images captured in the infrared spectrum allow to visually and non-destructively inspect the quality of photovoltaic (PV) modules. Currentl…