Implicit Sequence Learning - A Case Study with a 4-2-4 Encoder Simple Recurrent Network. - Stefan Glüge; Ronald Böck; Andreas Wendemuth (IJCCI (ICFC-ICNC), 2010)

A Simple Recurrent Network for Implicit Learning of Temporal Sequences. - Stefan Glüge; Oussama H. Hamid; Andreas Wendemuth (Cogn. Comput., 2010)

Segmented-Memory Recurrent Neural Networks versus Hidden Markov Models in Emotion Recognition from Speech. - Stefan Glüge; Ronald Böck; Andreas Wendemuth (IJCCI (NCTA), 2011)

A Markov Model of Conditional Associative Learning in a Cognitive Behavioural Scenario. - Stefan Glüge; Oussama H. Hamid; Jochen Braun; Andreas Wendemuth (IWINAC (1), 2011)

Intraindividual and interindividual multimodal emotion analyses in Human-Machine-Interaction. - Ronald Böck; Stefan Glüge; Andreas Wendemuth; Kerstin Limbrecht; Steffen Walter 001; David Hrabal; Harald C. Traue (CogSIMA, 2012)

Extension of Backpropagation through Time for Segmented-memory Recurrent Neural Networks. - Stefan Glüge; Ronald Böck; Andreas Wendemuth (IJCCI, 2012)

Annotation and Classification of Changes of Involvement in Group Conversation. - Ronald Böck; Stefan Glüge; Ingo Siegert; Andreas Wendemuth (ACII, 2013)

Auto-encoder pre-training of segmented-memory recurrent neural networks. - Stefan Glüge; Ronald Böck; Andreas Wendemuth (ESANN, 2013)

Dempster-Shafer Theory with Smoothness. - Ronald Böck; Stefan Glüge; Andreas Wendemuth (IUKM, 2013)

Solving Number Series with Simple Recurrent Networks. - Stefan Glüge; Andreas Wendemuth (IWINAC (1), 2013)

Implicit sequence learning in recurrent neural networks. - Stefan Glüge (2013)

Learning long-term dependencies in segmented-memory recurrent neural networks with backpropagation of error. - Stefan Glüge; Ronald Böck; Günther Palm; Andreas Wendemuth (Neurocomputing, 2014)

Emotion Recognition from Speech using Representation Learning in Extreme Learning Machines. - Stefan Glüge; Ronald Böck; Thomas Ott (IJCCI, 2017)

Economic Measures of Forecast Accuracy for Demand Planning: A Case-Based Discussion. - Thomas Ott; Stefan Glüge; Richard Bödi; Peter Kauf (Applied Data Science, 2019)

How (Not) to Measure Bias in Face Recognition Networks. - Stefan Glüge; Mohammadreza Amirian; Dandolo Flumini; Thilo Stadelmann (ANNPR, 2020)

Explainable Deep Learning for Medical Time Series Data. - Thomas Frick; Stefan Glüge; Abbas Rahimi; Luca Benini; Thomas Brunschwiler (MobiHealth, 2020)

Radiomics approach to quantify shape irregularity from crowd-based qualitative assessment of intracranial aneurysms. - Norman Juchler; Sabine Schilling; Stefan Glüge; Philippe Bijlenga; Daniel A. Rüfenacht; Vartan Kurtcuoglu; Sven Hirsch (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020)

Bias, awareness, and ignorance in deep-learning-based face recognition. - Samuel Wehrli; Corinna Hertweck; Mohammadreza Amirian; Stefan Glüge; Thilo Stadelmann (AI Ethics, 2022)

Robust Drone Detection and Classification from Radio Frequency Signals Using Convolutional Neural Networks. - Stefan Glüge; Matthias Nyfeler; Nicola Ramagnano; Claus Horn; Christof Schüpbach (IJCCI, 2023)

Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network. - Loïc Azzalini; Stefan Glüge; Jens Struckmeier; Yulia Sandamirskaya (ICANN (10), 2024)

Robust Low-Cost Drone Detection and Classification in Low SNR Environments. - Stefan Glüge; Matthias Nyfeler; Ahmad Aghaebrahimian; Nicola Ramagnano; Christof Schüpbach (CoRR, 2024)

Evaluation of deep learning training strategies for the classification of bone marrow cell images. - Stefan Glüge; Stefan Balabanov; Viktor H. Koelzer; Thomas Ott (Comput. Methods Programs Biomed., 2024)