activity
20152022
most citedOn the Explanation of Machine Learning Predictions in Clinical Gait Analysis

76 citations · 424 across the 21 of their papers we have counts for

collaborators

25 papers

cs.CV2022★ 1 cited

Explaining YOLO: Leveraging Grad-CAM to Explain Object Detections

Armin Kirchknopf, Djordje Slijepcevic, Ilkay Wunderlich +3

We investigate the problem of explainability for visual object detectors. Specifically, we demonstrate on the example of the YOLO object detector how to integrate Grad-CAM into the…

cs.CV2022

Real Estate Attribute Prediction from Multiple Visual Modalities with Missing Data

Eric Stumpe, Miroslav Despotovic, Zedong Zhang +1

The assessment and valuation of real estate requires large datasets with real estate information. Unfortunately, real estate databases are usually sparse in practice, i.e., not for…

cs.LG2022★ 11 cited

Explaining machine learning models for age classification in human gait analysis

Djordje Slijepcevic, Fabian Horst, Marvin Simak +7

Machine learning (ML) models have proven effective in classifying gait analysis data, e.g., binary classification of young vs. older adults. ML models, however, lack in providing h…

cs.LG2022★ 13 cited

Explaining automated gender classification of human gait

Fabian Horst, Djordje Slijepcevic, Matthias Zeppelzauer +6

State-of-the-art machine learning (ML) models are highly effective in classifying gait analysis data, however, they lack in providing explanations for their predictions. This "blac…

cs.HC2022★ 6 cited

Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy

Alexander Rind, Djordje Slijepčević, Matthias Zeppelzauer +3

Three-dimensional clinical gait analysis is essential for selecting optimal treatment interventions for patients with cerebral palsy (CP), but generates a large amount of time seri…

cs.CL2021★ 3 cited

Automatic Sexism Detection with Multilingual Transformer Models

Mina Schütz, Jaqueline Boeck, Daria Liakhovets +7

Sexism has become an increasingly major problem on social networks during the last years. The first shared task on sEXism Identification in Social neTworks (EXIST) at IberLEF 2021…