no code implementations • 9 Jun 2023 • Alessandro Wollek, Philip Haitzer, Thomas Sedlmeyr, Sardi Hyska, Johannes Rueckel, Bastian Sabel, Michael Ingrisch, Tobias Lasser
In this work, we explore the potential of weak supervision of a deep learning-based label prediction model, using a rule-based labeler.
no code implementations • 9 Jun 2023 • Alessandro Wollek, Sardi Hyska, Bastian Sabel, Michael Ingrisch, Tobias Lasser
Deep learning models for image classification are often trained at a resolution of 224 x 224 pixels for historical and efficiency reasons.
no code implementations • 9 Jun 2023 • Alessandro Wollek, Sardi Hyska, Bastian Sabel, Michael Ingrisch, Tobias Lasser
Finally, we propose and evaluate WindowNet, a model that learns optimal window settings, and show that it significantly improves performance compared to the baseline model without windowing.
no code implementations • 5 Jun 2023 • Alessandro Wollek, Sardi Hyska, Thomas Sedlmeyr, Philip Haitzer, Johannes Rueckel, Bastian O. Sabel, Michael Ingrisch, Tobias Lasser
This study aimed to develop an algorithm to automatically extract annotations for chest X-ray classification models from German thoracic radiology reports.