9 citations · 16 across the 10 of their papers we have counts for
19 papers
EasyMLServe: Easy Deployment of REST Machine Learning Services
Oliver Neumann, Marcel Schilling, Markus Reischl +1
Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and…
Exploiting Multiple EEG Data Domains with Adversarial Learning
David Bethge, Philipp Hallgarten, Ozan Özdenizci +3
Electroencephalography (EEG) is shown to be a valuable data source for evaluating subjects' mental states. However, the interpretation of multi-modal EEG signals is challenging, as…
ciscNet -- A Single-Branch Cell Instance Segmentation and Classification Network
Moritz Böhland, Oliver Neumann, Marcel P. Schilling +4
Automated cell nucleus segmentation and classification are required to assist pathologists in their decision making. The Colon Nuclei Identification and Counting Challenge 2022 (Co…
Concepts for Automated Machine Learning in Smart Grid Applications
Stefan Meisenbacher, Janik Pinter, Tim Martin +2
Undoubtedly, the increase of available data and competitive machine learning algorithms has boosted the popularity of data-driven modeling in energy systems. Applications are forec…
pyWATTS: Python Workflow Automation Tool for Time Series
Benedikt Heidrich, Andreas Bartschat, Marian Turowski +7
Time series data are fundamental for a variety of applications, ranging from financial markets to energy systems. Due to their importance, the number and complexity of tools and me…
Probabilistic Solar Power Forecasting: Long Short-Term Memory Network vs Simpler Approaches
Vinayak Sharma, Jorge Angel Gonzalez Ordiano, Ralf Mikut +1
The high penetration of volatile renewable energy sources such as solar make methods for coping with the uncertainty associated with them of paramount importance. Probabilistic for…