From the 1 of 7 linked papers with an AI index.
7 papers
Improving Wind and Solar Power Prediction with Efficient Wrapper-based Feature Selection: An Empirical Study
Daniel Grillmeyer, Marius Hadry, Michael Stenger +3
The paper introduces a clustering‑based wrapper method (CSFS) for automatically selecting input variables in wind and solar power forecasting, showing comparable accuracy to standa…
Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection
Robert Leppich, Michael Stenger, André Bauer +1
With the advent of Transformers, time series forecasting has seen significant advances, yet it remains challenging due to the need for effective sequence representation, memory con…
WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care
Vanessa Borst, Timo Dittus, Tassilo Dege +2
Chronic wounds affect a large population, particularly the elderly and diabetic patients, who often exhibit limited mobility and co-existing health conditions. Automated wound moni…
WoundAIssist: A Patient-Centered Mobile App for AI-Assisted Wound Care With Physicians in the Loop
Vanessa Borst, Anna Riedmann, Tassilo Dege +4
The rising prevalence of chronic wounds, especially in aging populations, presents a significant healthcare challenge due to prolonged hospitalizations, elevated costs, and reduced…
STEB: In Search of the Best Evaluation Approach for Synthetic Time Series
Michael Stenger, Robert Leppich, André Bauer +1
The growing need for synthetic time series, due to data augmentation or privacy regulations, has led to numerous generative models, frameworks, and evaluation measures alike. Objec…
TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and Imputation
Robert Leppich, Michael Stenger, Daniel Grillmeyer +2
We introduce a temporal feature encoding architecture called Time Series Representation Model (TSRM) for multivariate time series forecasting and imputation. The architecture is st…