52 citations · 69 across the 10 of their papers we have counts for
11 papers
ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP
Philipp Kohl, Nils Freyer, Yoka Krämer +5
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate t…
Predicting resolved galaxy properties from photometric images using convolutional neural networks
Tobias Buck, Steffen Wolf
Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as…
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks
Alberto Bailoni, Constantin Pape, Steffen Wolf +2
This work introduces a new proposal-free instance segmentation method that builds on single-instance segmentation masks predicted across the entire image in a sliding window style.…
Instance Separation Emerges from Inpainting
Steffen Wolf, Fred A. Hamprecht, Jan Funke
Deep neural networks trained to inpaint partially occluded images show a deep understanding of image composition and have even been shown to remove objects from images convincingly…
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation
Steffen Wolf, Yuyan Li, Constantin Pape +3
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label. In commonly used pipeline…
Learning the Arrow of Time
Nasim Rahaman, Steffen Wolf, Anirudh Goyal +2
We humans seem to have an innate understanding of the asymmetric progression of time, which we use to efficiently and safely perceive and manipulate our environment. Drawing inspir…