4 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
WoundAIssist: Development and Evaluation of an AI-Based Mobile Application for Remote Chronic Wound Care in Elderly Patients
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…
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…