Search Results for author: Steffen Illium

Found 16 papers, 2 papers with code

Improving Primate Sounds Classification using Binary Presorting for Deep Learning

no code implementations28 Jun 2023 Michael Kölle, Steffen Illium, Maximilian Zorn, Jonas Nüßlein, Patrick Suchostawski, Claudia Linnhoff-Popien

In the field of wildlife observation and conservation, approaches involving machine learning on audio recordings are becoming increasingly popular.

Data Augmentation Multi-class Classification

Compression of GPS Trajectories using Autoencoders

no code implementations18 Jan 2023 Michael Kölle, Steffen Illium, Carsten Hahn, Lorenz Schauer, Johannes Hutter, Claudia Linnhoff-Popien

The ubiquitous availability of mobile devices capable of location tracking led to a significant rise in the collection of GPS data.

Dynamic Time Warping

Empirical Analysis of Limits for Memory Distance in Recurrent Neural Networks

no code implementations20 Dec 2022 Steffen Illium, Thore Schillman, Robert Müller, Thomas Gabor, Claudia Linnhoff-Popien

Common to all different kinds of recurrent neural networks (RNNs) is the intention to model relations between data points through time.

Constructing Organism Networks from Collaborative Self-Replicators

no code implementations20 Dec 2022 Steffen Illium, Maximilian Zorn, Cristian Lenta, Michael Kölle, Claudia Linnhoff-Popien, Thomas Gabor

We introduce organism networks, which function like a single neural network but are composed of several neural particle networks; while each particle network fulfils the role of a single weight application within the organism network, it is also trained to self-replicate its own weights.

Visual Transformers for Primates Classification and Covid Detection

no code implementations20 Dec 2022 Steffen Illium, Robert Müller, Andreas Sedlmeier, Claudia-Linnhoff Popien

We apply the vision transformer, a deep machine learning model build around the attention mechanism, on mel-spectrogram representations of raw audio recordings.

Audio Classification Data Augmentation

VoronoiPatches: Evaluating A New Data Augmentation Method

no code implementations20 Dec 2022 Steffen Illium, Gretchen Griffin, Michael Kölle, Maximilian Zorn, Jonas Nüßlein, Claudia Linnhoff-Popien

We primarily utilize non-linear recombination of information within an image, fragmenting and occluding small information patches.

Data Augmentation

Case-Based Inverse Reinforcement Learning Using Temporal Coherence

1 code implementation12 Jun 2022 Jonas Nüßlein, Steffen Illium, Robert Müller, Thomas Gabor, Claudia Linnhoff-Popien

As a prior, we assume that the higher-level strategy is to reach an unknown target state area, which we hypothesize is a valid prior for many domains in Reinforcement Learning.

Imitation Learning reinforcement-learning +2

Analysis of Feature Representations for Anomalous Sound Detection

no code implementations11 Dec 2020 Robert Müller, Steffen Illium, Fabian Ritz, Kyrill Schmid

In this work, we thoroughly evaluate the efficacy of pretrained neural networks as feature extractors for anomalous sound detection.

Acoustic Leak Detection in Water Networks

no code implementations11 Dec 2020 Robert Müller, Steffen Illium, Fabian Ritz, Tobias Schröder, Christian Platschek, Jörg Ochs, Claudia Linnhoff-Popien

In this work, we present a general procedure for acoustic leak detection in water networks that satisfies multiple real-world constraints such as energy efficiency and ease of deployment.

Anomaly Detection

Policy Entropy for Out-of-Distribution Classification

no code implementations25 May 2020 Andreas Sedlmeier, Robert Müller, Steffen Illium, Claudia Linnhoff-Popien

One critical prerequisite for the deployment of reinforcement learning systems in the real world is the ability to reliably detect situations on which the agent was not trained.

Benchmarking Classification +5

Trajectory annotation using sequences of spatial perception

no code implementations11 Apr 2020 Sebastian Feld, Steffen Illium, Andreas Sedlmeier, Lenz Belzner

In the near future, more and more machines will perform tasks in the vicinity of human spaces or support them directly in their spatially bound activities.

Soccer Team Vectors

no code implementations30 Jul 2019 Robert Müller, Stefan Langer, Fabian Ritz, Christoph Roch, Steffen Illium, Claudia Linnhoff-Popien

In this work we present STEVE - Soccer TEam VEctors, a principled approach for learning real valued vectors for soccer teams where similar teams are close to each other in the resulting vector space.

BIG-bench Machine Learning

Deep Neural Baselines for Computational Paralinguistics

no code implementations5 Jul 2019 Daniel Elsner, Stefan Langer, Fabian Ritz, Robert Müller, Steffen Illium

Detecting sleepiness from spoken language is an ambitious task, which is addressed by the Interspeech 2019 Computational Paralinguistics Challenge (ComParE).

Audio Classification BIG-bench Machine Learning +1

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