Filtering Relevant Facebook Status Updates for Users of Mobile Devices. - Stephan Baumann 001; Rafael Schirru; Joachim Folz (ICAART (1), 2013)

Towards Extraction of Subjective Reading Incomprehension: Analysis of Eye Gaze Features. - Ayano Okoso; Takumi Toyama; Kai Kunze; Joachim Folz; Marcus Liwicki; Koichi Kise (CHI Extended Abstracts, 2015)

Extraction of read text using a wearable eye tracker for automatic video annotation. - Mizuki Matsubara; Joachim Folz; Takumi Toyama; Marcus Liwicki; Andreas Dengel 001; Koichi Kise (UbiComp/ISWC Adjunct, 2015)

Aesthetic Photo Enhancement using Machine Learning and Case-Based Reasoning. - Joachim Folz; Christian Schulze 001; Damian Borth; Andreas Dengel 001 (ASM@ACM Multimedia, 2015)

An Evolutionary Algorithm to Learn SPARQL Queries for Source-Target-Pairs - Finding Patterns for Human Associations in DBpedia. - Jörn Hees; Rouven Bauer; Joachim Folz; Damian Borth; Andreas Dengel 001 (EKAW, 2016)

Edinburgh Associative Thesaurus as RDF and DBpedia Mapping. - Jörn Hees; Rouven Bauer; Joachim Folz; Damian Borth; Andreas Dengel 001 (ESWC (Satellite Events), 2016)

Erratum to: Edinburgh Associative Thesaurus as RDF and DBpedia Mapping. - Jörn Hees; Rouven Bauer; Joachim Folz; Damian Borth; Andreas Dengel 001 (ESWC (Satellite Events), 2016)

Hybrid Teams of Humans, Robots, and Virtual Agents in a Production Setting. - Tim Schwartz; Michael Feld; Christian Bürckert; Svilen Dimitrov; Joachim Folz; Dieter Hutter; Peter Hevesi; Bernd Kiefer; Hans-Ulrich Krieger; Christoph Lüth; Dennis Mronga; Gerald Pirkl; et al. (Intelligent Environments, 2016)

Hybrid Teams: Flexible Collaboration Between Humans, Robots and Virtual Agents. - Tim Schwartz; Ingo Zinnikus; Hans-Ulrich Krieger; Christian Bürckert; Joachim Folz; Bernd Kiefer; Peter Hevesi; Christoph Lüth; Gerald Pirkl; Torsten Spieldenner; Norbert Schmitz; Malte Wirkus; et al. (MATES, 2016)

Predicting Human Associations with Graph Patterns Learned from Linked Data. - Jörn Hees; Rouven Bauer; Joachim Folz; Damian Borth; Andreas Dengel 001 (ISWC (Posters, Demos & Industry Tracks), 2017)

What Do Deep Networks Like to See? - Sebastian Palacio; Joachim Folz; Jörn Hees; Federico Raue; Damian Borth; Andreas Dengel 001 (CVPR, 2018)

Adversarial Defense based on Structure-to-Signal Autoencoders. - Joachim Folz; Sebastian Palacio; Jörn Hees; Damian Borth; Andreas Dengel 001 (CoRR, 2018)

Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks. - Benjamin Bischke; Patrick Helber; Joachim Folz; Damian Borth; Andreas Dengel 001 (ICIP, 2019)

P ≈ NP, at least in Visual Question Answering. - Shailza Jolly; Sebastian Palacio; Joachim Folz; Federico Raue; Jörn Hees; Andreas Dengel 001 (ICPR, 2020)

Adversarial Defense based on Structure-to-Signal Autoencoders. - Joachim Folz; Sebastian Palacio; Jörn Hees; Andreas Dengel 001 (WACV, 2020)

Training Deep Neural Networks Without Batch Normalization. - Divya Gaur; Joachim Folz; Andreas Dengel 001 (CoRR, 2020)

A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances. - Brian B. Moser; Arundhati S. Shanbhag; Stanislav Frolov; Federico Raue; Joachim Folz; Andreas Dengel 001 (CoRR, 2025)