Search Results for author: Matthias Zeppelzauer

Found 27 papers, 5 papers with code

3D Multimodal Image Registration for Plant Phenotyping

1 code implementation3 Jul 2024 Eric Stumpe, Gernot Bodner, Francesco Flagiello, Matthias Zeppelzauer

By leveraging depth data, our method mitigates parallax effects and thus facilitates more accurate pixel alignment across camera modalities.

Image Registration Plant Phenotyping

Case Study: Ensemble Decision-Based Annotation of Unconstrained Real Estate Images

no code implementations26 Sep 2023 Miroslav Despotovic, Zedong Zhang, Eric Stumpe, Matthias Zeppelzauer

We describe a proof-of-concept for annotating real estate images using simple iterative rule-based semi-supervised learning.

Real Estate Attribute Prediction from Multiple Visual Modalities with Missing Data

no code implementations16 Nov 2022 Eric Stumpe, Miroslav Despotovic, Zedong Zhang, Matthias Zeppelzauer

Furthermore, the fusion of information from indoor and outdoor photos results in a performance boost of up to 5% in Macro F1-score.

Attribute

Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy

no code implementations10 Aug 2022 Alexander Rind, Djordje Slijepčević, Matthias Zeppelzauer, Fabian Unglaube, Andreas Kranzl, Brian Horsak

Three-dimensional clinical gait analysis is essential for selecting optimal treatment interventions for patients with cerebral palsy (CP), but generates a large amount of time series data.

Classification Explainable artificial intelligence +2

Multimodal Detection of Information Disorder from Social Media

no code implementations31 May 2021 Armin Kirchknopf, Djordje Slijepcevic, Matthias Zeppelzauer

Social media is accompanied by an increasing proportion of content that provides fake information or misleading content, known as information disorder.

Fake News Detection

Bounded logit attention: Learning to explain image classifiers

1 code implementation31 May 2021 Thomas Baumhauer, Djordje Slijepcevic, Matthias Zeppelzauer

Explainable artificial intelligence is the attempt to elucidate the workings of systems too complex to be directly accessible to human cognition through suitable side-information referred to as "explanations".

Explainable artificial intelligence feature selection +2

$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers

1 code implementation9 Feb 2021 Djordje Slijepčević, Maximilian Henzl, Lukas Daniel Klausner, Tobias Dam, Peter Kieseberg, Matthias Zeppelzauer

For use with anonymisation techniques, the $k$-anonymity criterion is one of the most popular, with numerous scientific publications on different algorithms and metrics.

BIG-bench Machine Learning

Machine Unlearning: Linear Filtration for Logit-based Classifiers

no code implementations7 Feb 2020 Thomas Baumhauer, Pascal Schöttle, Matthias Zeppelzauer

Recently enacted legislation grants individuals certain rights to decide in what fashion their personal data may be used, and in particular a "right to be forgotten".

Machine Unlearning

Persistence Bag-of-Words for Topological Data Analysis

1 code implementation21 Dec 2018 Bartosz Zieliński, Michał Lipiński, Mateusz Juda, Matthias Zeppelzauer, Paweł Dłotko

Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs).

BIG-bench Machine Learning Topological Data Analysis

Automatic Prediction of Building Age from Photographs

no code implementations6 Apr 2018 Matthias Zeppelzauer, Miroslav Despotovic, Muntaha Sakeena, David Koch, Mario Döller

We present a first method for the automated age estimation of buildings from unconstrained photographs.

Age Estimation

Persistence Codebooks for Topological Data Analysis

no code implementations13 Feb 2018 Bartosz Zielinski, Michal Lipinski, Mateusz Juda, Matthias Zeppelzauer, Pawel Dlotko

Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs) which are 2D multisets of points.

BIG-bench Machine Learning Quantization +1

Automatic Classification of Functional Gait Disorders

no code implementations18 Dec 2017 Djordje Slijepcevic, Matthias Zeppelzauer, Anna-Maria Gorgas, Caterine Schwab, Michael Schüller, Arnold Baca, Christian Breiteneder, Brian Horsak

The aim of the study is twofold: (1) to investigate the suitability of stateof-the-art GRF parameterization techniques (representations) for the discrimination of functional gait disorders; and (2) to provide a first performance baseline for the automated classification of functional gait disorders for a large-scale dataset.

Classification General Classification +1

A Study on Topological Descriptors for the Analysis of 3D Surface Texture

no code implementations29 Oct 2017 Matthias Zeppelzauer, Bartosz Zielinski, Mateusz Juda, Markus Seidl

Methods from computational topology are becoming more and more popular in computer vision and have shown to improve the state-of-the-art in several tasks.

General Classification

PetroSurf3D - A Dataset for high-resolution 3D Surface Segmentation

no code implementations6 Oct 2016 Georg Poier, Markus Seidl, Matthias Zeppelzauer, Christian Reinbacher, Martin Schaich, Giovanna Bellandi, Alberto Marretta, Horst Bischof

The development of powerful 3D scanning hardware and reconstruction algorithms has strongly promoted the generation of 3D surface reconstructions in different domains.

Interactive Segmentation Segmentation +1

Topological descriptors for 3D surface analysis

no code implementations22 Jan 2016 Matthias Zeppelzauer, Bartosz Zieliński, Mateusz Juda, Markus Seidl

We investigate topological descriptors for 3D surface analysis, i. e. the classification of surfaces according to their geometric fine structure.

Classification General Classification

Multimodal Classification of Events in Social Media

no code implementations4 Jan 2016 Matthias Zeppelzauer, Daniel Schopfhauser

The task of social event classification refers to the distinction of event and non-event-related content as well as the classification of event types (e. g. sports events, concerts, etc.).

Classification General Classification

Efficient Image-Space Extraction and Representation of 3D Surface Topography

no code implementations30 Apr 2015 Matthias Zeppelzauer, Markus Seidl

Surface topography refers to the geometric micro-structure of a surface and defines its tactile characteristics (typically in the sub-millimeter range).

3D Reconstruction Classification +1

Cultural Event Recognition with Visual ConvNets and Temporal Models

no code implementations24 Apr 2015 Amaia Salvador, Matthias Zeppelzauer, Daniel Manchon-Vizuete, Andrea Calafell, Xavier Giro-i-Nieto

Our solution is based on the combination of visual features extracted from convolutional neural networks with temporal information using a hierarchical classifier scheme.

Classification General Classification

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