1 code implementation • 7 Nov 2022 • Anna Breger, Clemens Karner, Martin Ehler
The code is made available on GitHub and straightforward to use.
no code implementations • 13 Sep 2021 • Anna Breger, Felix Goldbach, Bianca S. Gerendas, Ursula Schmidt-Erfurth, Martin Ehler
The results underline the visual evaluation.
no code implementations • 2 Aug 2019 • José Ignacio Orlando, Anna Breger, Hrvoje Bogunović, Sophie Riedl, Bianca S. Gerendas, Martin Ehler, Ursula Schmidt-Erfurth
Supervised deep learning models trained with standard loss functions are usually able to characterize only the most common disease appeareance from a training set, resulting in suboptimal performance and poor generalization when dealing with unseen lesions.
2 code implementations • 21 Mar 2019 • Pavol Harar, Roswitha Bammer, Anna Breger, Monika Dörfler, Zdenek Smekal
In this contribution we investigate how input and target representations interplay with the amount of available training data in a music information retrieval setting.
1 code implementation • 22 Jan 2019 • Anna Breger, Jose Ignacio Orlando, Pavol Harar, Monika Dörfler, Sophie Klimscha, Christoph Grechenig, Bianca S. Gerendas, Ursula Schmidt-Erfurth, Martin Ehler
In two supervised learning problems, clinical image segmentation and music information classification, the application of our proposed augmented target loss functions increase the accuracy.