no code implementations • 13 Dec 2023 • Clemens Seibold, Anna Hilsmann, Peter Eisert
Furthermore, we show that our approach does not impair the biometric quality, which is essential for high quality morphs.
no code implementations • 1 Feb 2022 • Clemens Seibold, Johannes Künzel, Anna Hilsmann, Peter Eisert
The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision.
Explainable Artificial Intelligence (XAI) Image Segmentation +3
no code implementations • 30 Nov 2021 • Aleixo Cambeiro Barreiro, Clemens Seibold, Anna Hilsmann, Peter Eisert
Recently, the use of drones or helicopters for remote recording is increasing in the industry, sparing the technicians this perilous task.
no code implementations • 26 Mar 2021 • Clemens Seibold, Anna Hilsmann, Peter Eisert
This evaluation framework is based on removing detected artifacts and analyzing the influence of these changes on the decision of the DNN.
no code implementations • 23 Apr 2020 • Clemens Seibold, Anna Hilsmann, Peter Eisert
A morphed face image is a synthetically created image that looks so similar to the faces of two subjects that both can use it for verification against a biometric verification system.
no code implementations • 5 Jul 2018 • Clemens Seibold, Anna Hilsmann, Peter Eisert
This map is compared with the highlights in the image that is suspected to be a fraud.
no code implementations • 11 Jun 2018 • Clemens Seibold, Wojciech Samek, Anna Hilsmann, Peter Eisert
Artificial neural networks tend to learn only what they need for a task.