11 citations · 30 across the 5 of their papers we have counts for
4 papers · 1 filter
Hybrid adiabatic quantum computing for tomographic image reconstruction -- opportunities and limitations
Merlin A. Nau, A. Hans Vija, Wesley Gohn +2
Our goal is to reconstruct tomographic images with few measurements and a low signal-to-noise ratio. In clinical imaging, this helps to improve patient comfort and reduce radiation…
SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for prior-informed assessment of muscle function and pathology
Alexander Mühlberg, Paul Ritter, Simon Langer +11
Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as a black box, exclude biomedical experts, and need extensive data. We introduce t…
DeepFilterNet2: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio
Hendrik Schröter, Alberto N. Escalante-B., Tobias Rosenkranz +1
Deep learning-based speech enhancement has seen huge improvements and recently also expanded to full band audio (48 kHz). However, many approaches have a rather high computational…
Effect of Random Histogram Equalization on Breast Calcification Analysis Using Deep Learning
Adarsh Bhandary Panambur, Prathmesh Madhu, Andreas Maier
Early detection and analysis of calcifications in mammogram images is crucial in a breast cancer diagnosis workflow. Management of calcifications that require immediate follow-up a…