264 citations · 501 across the 15 of their papers we have counts for
5 papers · 1 filter
Out of distribution detection for intra-operative functional imaging
Tim J. Adler, Leonardo Ayala, Lynton Ardizzone +6
Multispectral optical imaging is becoming a key tool in the operating room. Recent research has shown that machine learning algorithms can be used to convert pixel-wise reflectance…
Object Segmentation using Pixel-wise Adversarial Loss
Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe +1
Recent deep learning based approaches have shown remarkable success on object segmentation tasks. However, there is still room for further improvement. Inspired by generative adver…
Guided Image Generation with Conditional Invertible Neural Networks
Lynton Ardizzone, Carsten Lüth, Jakob Kruse +2
In this work, we address the task of natural image generation guided by a conditioning input. We introduce a new architecture called conditional invertible neural network (cINN). T…
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning
Steffen Wolf, Alberto Bailoni, Constantin Pape +4
Image partitioning, or segmentation without semantics, is the task of decomposing an image into distinct segments, or equivalently to detect closed contours. Most prior work either…
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks
Tim J. Adler, Lynton Ardizzone, Anant Vemuri +8
Purpose: Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to addres…