no code implementations • 3 Mar 2025 • Peng Yan, Ahmed Abdulkadir, Gerrit A. Schatte, Giulia Aguzzi, Joonsu Gha, Nikola Pascher, Matthias Rosenthal, Yunlong Gao, Benjamin F. Grewe, Thilo Stadelmann
To go from (passive) process monitoring to active process control, an effective AI system must learn about the behavior of the complex system from very limited training data, forming an ad-hoc digital twin with respect to process in- and outputs that captures the consequences of actions on the process's world.
1 code implementation • 15 Feb 2025 • Matteo Saponati, Pascal Sager, Pau Vilimelis Aceituno, Thilo Stadelmann, Benjamin Grewe
Self-attention is essential to Transformer architectures, yet how information is embedded in the self-attention matrices and how different objective functions impact this process remains unclear.
no code implementations • 27 Jan 2025 • Pascal J. Sager, Benjamin Meyer, Peng Yan, Rebekka von Wartburg-Kottler, Layan Etaiwi, Aref Enayati, Gabriel Nobel, Ahmed Abdulkadir, Benjamin F. Grewe, Thilo Stadelmann
Instruction-based computer control agents (CCAs) execute complex action sequences on personal computers or mobile devices to fulfill tasks using the same graphical user interfaces as a human user would, provided instructions in natural language.
1 code implementation • 8 Jul 2024 • Pascal J. Sager, Jan M. Deriu, Benjamin F. Grewe, Thilo Stadelmann, Christoph von der Malsburg
We introduce the Cooperative Network Architecture (CNA), a model that represents sensory signals using structured, recurrently connected networks of neurons, termed "nets."
1 code implementation • 21 Apr 2024 • Felix M. Schmitt-Koopmann, Elaine M. Huang, Hans-Peter Hutter, Thilo Stadelmann, Alireza Darvishy
Based on this process, we developed an improved version of the benchmark dataset im2latex-100k, featuring 30 fonts instead of one.
no code implementations • 14 Nov 2023 • Lukas Tuggener, Thilo Stadelmann, Jürgen Schmidhuber
Humans and animals recognize objects irrespective of the beholder's point of view, which may drastically change their appearances.
no code implementations • 1 Nov 2023 • Daniel Neururer, Volker Dellwo, Thilo Stadelmann
While deep neural networks have shown impressive results in automatic speaker recognition and related tasks, it is dissatisfactory how little is understood about what exactly is responsible for these results.
no code implementations • 11 Jul 2023 • Peng Yan, Ahmed Abdulkadir, Paul-Philipp Luley, Matthias Rosenthal, Gerrit A. Schatte, Benjamin F. Grewe, Thilo Stadelmann
However, due to the dynamic nature of the industrial processes and environment, it is impractical to acquire large-scale labeled data for standard deep learning training for every slightly different case anew.
1 code implementation • 26 Jun 2023 • Raphael Emberger, Jens Michael Boss, Daniel Baumann, Marko Seric, Shufan Huo, Lukas Tuggener, Emanuela Keller, Thilo Stadelmann
In this paper, we propose a new method for exploiting information in the temporal succession of video frames.
1 code implementation • IEEE Access 2022 • Felix M. Schmitt-Koopmann, Elaine M. Huang, Hans-Peter Hutter, Thilo Stadelmann, Alireza Darvishy
At over 45k pages, we believe that FormulaNet is the largest MFD dataset with inline formula labels.
no code implementations • 24 Aug 2022 • Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann
The existence of adversarial attacks on convolutional neural networks (CNN) questions the fitness of such models for serious applications.
no code implementations • 19 Aug 2022 • Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss, Yves D. Stebler, Ahmet Selman Bozkir, Marco Calandri, Friedhelm Schwenker, Thilo Stadelmann
With the spread of COVID-19 over the world, the need arose for fast and precise automatic triage mechanisms to decelerate the spread of the disease by reducing human efforts e. g. for image-based diagnosis.
no code implementations • 22 Apr 2022 • Christoph von der Malsburg, Thilo Stadelmann, Benjamin F. Grewe
Introduction: In contrast to current AI technology, natural intelligence -- the kind of autonomous intelligence that is realized in the brains of animals and humans to attain in their natural environment goals defined by a repertoire of innate behavioral schemata -- is far superior in terms of learning speed, generalization capabilities, autonomy and creativity.
1 code implementation • 16 Mar 2021 • Lukas Tuggener, Jürgen Schmidhuber, Thilo Stadelmann
In this work we challenge the notion that CNN architecture design solely based on ImageNet leads to generally effective convolutional neural network (CNN) architectures that perform well on a diverse set of datasets and application domains.
no code implementations • 28 Apr 2020 • Dano Roost, Ralph Meier, Stephan Huschauer, Erik Nygren, Adrian Egli, Andreas Weiler, Thilo Stadelmann
We present preliminary results from our sixth placed entry to the Flatland international competition for train rescheduling, including two improvements for optimized reinforcement learning (RL) training efficiency, and two hypotheses with respect to the prospect of deep RL for complex real-world control tasks: first, that current state of the art policy gradient methods seem inappropriate in the domain of high-consequence environments; second, that learning explicit communication actions (an emerging machine-to-machine language, so to speak) might offer a remedy.
no code implementations • 19 Jul 2019 • Lukas Tuggener, Mohammadreza Amirian, Katharina Rombach, Stefan Lörwald, Anastasia Varlet, Christian Westermann, Thilo Stadelmann
A main driver behind the digitization of industry and society is the belief that data-driven model building and decision making can contribute to higher degrees of automation and more informed decisions.
1 code implementation • 12 Oct 2018 • Ismail Elezi, Lukas Tuggener, Marcello Pelillo, Thilo Stadelmann
This paper gives an overview of our current Optical Music Recognition (OMR) research.
no code implementations • 13 Jul 2018 • Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci, Marek Arnold, Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger, Stefan Lörwald, Benjamin Bruno Meier, Katharina Rombach, Lukas Tuggener
Deep learning with neural networks is applied by an increasing number of people outside of classic research environments, due to the vast success of the methodology on a wide range of machine perception tasks.
1 code implementation • 11 Jul 2018 • Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Durr, Thilo Stadelmann
We propose a novel end-to-end neural network architecture that, once trained, directly outputs a probabilistic clustering of a batch of input examples in one pass.
no code implementations • 26 May 2018 • Lukas Tuggener, Ismail Elezi, Jurgen Schmidhuber, Thilo Stadelmann
Optical Music Recognition (OMR) is an important and challenging area within music information retrieval, the accurate detection of music symbols in digital images is a core functionality of any OMR pipeline.
1 code implementation • 21 May 2018 • Feliks Hibraj, Sebastiano Vascon, Thilo Stadelmann, Marcello Pelillo
We report on a comprehensive set of experiments on the TIMIT dataset against standard clustering techniques and specific speaker clustering methods.
Sound Audio and Speech Processing
2 code implementations • 27 Mar 2018 • Lukas Tuggener, Ismail Elezi, Jürgen Schmidhuber, Marcello Pelillo, Thilo Stadelmann
We present the DeepScores dataset with the goal of advancing the state-of-the-art in small objects recognition, and by placing the question of object recognition in the context of scene understanding.