10 citations · 26 across the 4 of their papers we have counts for
6 papers
Conifer Seedling Detection in UAV-Imagery with RGB-Depth Information
Jason Jooste, Michael Fromm, Matthias Schubert
Monitoring of reforestation is currently being considerably streamlined through the use of drones and image recognition algorithms, which have already proven to be effective on col…
Active Learning for Argument Strength Estimation
Nataliia Kees, Michael Fromm, Evgeniy Faerman +1
High-quality arguments are an essential part of decision-making. Automatically predicting the quality of an argument is a complex task that recently got much attention in argument…
Argument Mining Driven Analysis of Peer-Reviews
Michael Fromm, Evgeniy Faerman, Max Berrendorf +7
Peer reviewing is a central process in modern research and essential for ensuring high quality and reliability of published work. At the same time, it is a time-consuming process a…
Diversity Aware Relevance Learning for Argument Search
Michael Fromm, Max Berrendorf, Sandra Obermeier +2
In this work, we focus on the problem of retrieving relevant arguments for a query claim covering diverse aspects. State-of-the-art methods rely on explicit mappings between claims…
Unsupervised Anomaly Detection for X-Ray Images
Diana Davletshina, Valentyn Melnychuk, Viet Tran +5
Obtaining labels for medical (image) data requires scarce and expensive experts. Moreover, due to ambiguous symptoms, single images rarely suffice to correctly diagnose a medical c…
TACAM: Topic And Context Aware Argument Mining
Michael Fromm, Evgeniy Faerman, Thomas Seidl
In this work we address the problem of argument search. The purpose of argument search is the distillation of pro and contra arguments for requested topics from large text corpora.…