In volume rendering, transfer functions are used to classify structures ...
Deep learning in medical imaging has the potential to minimize the risk ...
Cluster separation in scatterplots is a task that is typically tackled b...
Large Language Models (LLMs) have revolutionized natural language proces...
State recognition in well-known and customizable environments such as
ve...
Indirect Time-of-Flight (iToF) cameras are a widespread type of 3D senso...
Neural networks have shown great success in extracting geometric informa...
A key to deciphering the inner workings of neural networks is understand...
Learning from 3D protein structures has gained wide interest in protein
...
We propose a new microscopy simulation system that can depict atomistic
...
Scanning Transmission Electron Microscopes (STEMs) acquire 2D images of ...
This paper proposes a novel method for deep learning based on the analyt...
While the need for well-trained, fair ML systems is increasing ever more...
Appropriate weight initialization has been of key importance to successf...
Time-of-Flight (ToF) cameras are subject to high levels of noise and
dis...
We propose the adjacency adaptive graph convolutional long-short term me...
Density estimation plays a crucial role in many data analysis tasks, as ...
We propose Blue Noise Plots, two-dimensional dot plots that depict data
...
Due to the success of deep learning and its growing job market, students...
We present a novel deep learning based technique for volumetric ambient
...
Proteins perform a large variety of functions in living organisms, thus
...
Research software has become a central asset in academic research. It
op...
Optimal viewpoint prediction is an essential task in many computer
graph...
This paper presents an empirical study on the weights of neural networks...
Many lighting methods used in computer graphics such as indirect illumin...
We show that denoising of 3D point clouds can be learned unsupervised,
d...
One of the grand challenges of deep learning is the requirement to obtai...
To properly convey neural network architectures in publications, appropr...
The complexity of today's visualization applications demands specific
vi...
We suggest a method to directly deep-learn light transport, i. e., the
m...
Convolutional neural networks gain more and more popularity in image
cla...
To enhance depth perception and thus data comprehension, additional dept...
We propose an efficient and effective method to learn convolutions for
n...
As many different 3D volumes could produce the same 2D x-ray image, inve...
Ultrasound is one of the most frequently used imaging modality in medici...