TY  - CHAP
A1  - Wöber, Wilfried
A1  - Kefer, Martin
A1  - Kubinger, Wilfried
A1  - Szuegyi, Daniel
T1  - Evaluation of Daylight and Thermal Infra-Red based Detection for Platooning Vehicles
T2  - Annals of DAAM for 2012 and Proceedings of the 23rd International DAAM Symposium
KW  - Vehicle
KW  - Thermal Detection
Y1  - 2019
SP  - 719
EP  - 722
ER  - 
TY  - CHAP
A1  - Steigl, D
A1  - Aburaia, Mohamed
A1  - Wöber, Wilfried
T1  - Autonomous Grasping of Known Objects Using Depth Data and the PCA
T2  - Austrian Robotics Workshop 2020
KW  - Robotic
KW  - Autonomous
KW  - Grasping
Y1  - 2020
ER  - 
TY  - CHAP
A1  - Schwaiger, Simon
A1  - Aburaia, Mohamed
A1  - Aburaia, Ali
A1  - Wöber, Wilfried
T1  - Explainable Artificial Intelligence for Robot Arm Control
T2  - Proceedings of the 32nd International DAAAM Virtual Symposium `Intelligent Manufacturing & Automation`, 28-29th October 2021, Vienna
KW  - Artificial Intelligence
KW  - Machine Learning
Y1  - 
VL  - 32
IS  - 1
SP  - 0640
EP  - 0647
ER  - 
TY  - CHAP
A1  - Kriegler, Andreas
A1  - Wöber, Wilfried
A1  - Aburaia, Mohamed
T1  - Artificial Neural Networks Based Place Categorization
T2  - Digital Conversion on the Way to Industry 4.0
KW  - Artificial Intelligence
Y1  - 
SP  - 201
EP  - 209
PB  - Springer Verlag
ER  - 
TY  - CHAP
A1  - Felber, Stefan Otto
A1  - Aburaia, Mohamed
A1  - Wöber, Wilfried
A1  - Lackner, Maximilian
T1  - Parameter Optimization for the 3D Print of Thermo-Plastic Pellets with an Industrial Robot
T2  - Digital Conversion on the Way to Industry 4.0
KW  - Thermo Plastics
KW  - Industrial Robot
Y1  - 
SP  - 236
EP  - 247
ER  - 
TY  - JOUR
A1  - Rauer, Johannes
A1  - Aburaia, Mohamed
A1  - Wöber, Wilfried
T1  - Semi-Automatic Generation of Training Data for Neural Networks for 6D Pose Estimation and Robotic Graspin
JF  - Proceedings of Joint Austrian Computer Vision and Robotics Workshop 2020
KW  - Robotics
KW  - Neural Networks
Y1  - 2020
SP  - 2
EP  - 3
ER  - 
TY  - CHAP
A1  - Abdank, Moritz
A1  - Aburaia, Mohamed
A1  - Wöber, Wilfried
T1  - Using-Colour-Based Object Detection for Pick and Place Applications
T2  - Proceedings of the 32nd International DAAAM Virtual Symposium 'Intelligent Manufacturing & Automation', 28-29th October 2021, Vienna
KW  - Computer Vision
KW  - Object Detection
KW  - ROS
Y1  - 
VL  - 32
IS  - 1
SP  - 0536
EP  - 0541
ER  - 
TY  - CHAP
A1  - Wöber, Wilfried
A1  - Aburaia, Ali
A1  - Aburaia, Mohamed
A1  - Kubinger, Wilfried
A1  - Otrebski, Richard
A1  - Engelhardt-Nowitzki, Corinna
A1  - Markl, Erich
T1  - Konferenz der Mechatronik-Plattform:  Autonome mechatronische Systeme
T2  - FH CAMPUS 02, 22. November 2018 Digital Manufacturing & Robotics im Department Industrial Engineering
KW  - Autonom
KW  - Mechatronic
Y1  - 2020
ER  - 
TY  - CHAP
A1  - Rauer, Johannes
A1  - Aburaia, Mohamed
A1  - Wöber, Wilfried
T1  - Semi-Automatic Generation of Training Data for Neural Networks for 6D Pose Estimation and Robotic Grasping
T2  - Austrian Robotics Workshop 2020
KW  - Semi-Automatic
KW  - Neural Network
KW  - Robotic
KW  - Grasping
KW  - 6D
Y1  - 2020
ER  - 
TY  - CHAP
A1  - Kefer, Martin
A1  - Wöber, Wilfried
A1  - Szuegyi, Daniel
A1  - Kubinger, Wilfried
T1  - A Novel and Automated Circle Pattern Recognition Technique for Infra-Red Stero Camera Calibration
T2  - Proceedings of the 10th IASTED International Conference on Signal Processing, Pattern Recognition and Applications
KW  - Pattern Recognition
KW  - Infra-Red Camera
Y1  - 2019
SP  - 404
EP  - 410
ER  - 
TY  - CHAP
A1  - Kriegler, Andreas
A1  - Wöber, Wilfried
T1  - Vision-based Docking of a Mobile Robot
T2  - Proceedings of the Joint Austrian Computer Vision and Robotics Workshop 2020
KW  - Automation
KW  - Robotics
Y1  - 
SP  - 6
EP  - 12
ER  - 
TY  - CHAP
A1  - Wöber, Wilfried
A1  - Novotny, Georg
A1  - Aburaia, Mohamed
A1  - Otrebski, Richard
A1  - Kubinger, Wilfried
T1  - Estimating a Sparse Representation of Gaussian Processes Using Global Optimization and the Bayesian Information Criterion
T2  - Austrian Robotics Workshop 2018
KW  - Mobile Robotics
KW  - Localizations
KW  - Gaussian process
KW  - Robotics
Y1  - 
ER  - 
TY  - CHAP
A1  - Wöber, Wilfried
A1  - Schulmeister, Klemens
A1  - Aschauer, Christian
A1  - Gronauer, Andreas
A1  - Tomic, Dana Kathrin
A1  - Fensel, Anna
A1  - Riegler, Thomas
A1  - Handler, Franz
A1  - Hörmann, Sandra
A1  - Otte, Marcel
A1  - Auer, Wolfgang
T1  - Adaptive Agricultural Processes via Open Interfaces and Linked Services
T2  - Referate der 34. GIL-Jahrestagung - IT-Standards in der Agrar- und Ernährungswissenschaft
KW  - Adaption
KW  - Agriculture
Y1  - 2019
SP  - 157
EP  - 160
ER  - 
TY  - CHAP
A1  - Rauer, Johannes
A1  - Wöber, Wilfried
A1  - Aburaia, Mohamed
T1  - An Autonomous Mobile Handling Robot Using Object Recognition
T2  - Proceedings of ARW & OAGM Workshop 2019
KW  - Mobile Robotics
Y1  - 2020
N1  - https://workshops.aapr.at/wp-content/uploads/2019/05/ARW-OAGM19_06.pdf
ER  - 
TY  - CHAP
A1  - Tomic, Dana Kathrin
A1  - Drenjanac, Domagoj
A1  - Lazendic, Goran
A1  - Hörmann, Sandra
A1  - Handler, Franz
A1  - Wöber, Wilfried
A1  - Schulmeister, Klemens
A1  - Otte, Marcel
A1  - Auer, Wolfgang
T1  - Semantic Services for Adaptive Processes in Livestock Farming
T2  - International Conference of Agricultural Engineering (AgEng 2014)
KW  - Agriculture
KW  - Semantic Services
KW  - Adaption
Y1  - 2019
ER  - 
TY  - JOUR
A1  - Tomic, Dana Kathrin
A1  - Drenjanac, Domagoj
A1  - Lazendic, Goran
A1  - Hörmann, Sandra
A1  - Handler, Franz
A1  - Wöber, Wilfried
A1  - Aschauer, Christian
A1  - Auer, Wolfgang
T1  - Ontologies and semantic services for process optimization in agricultural production
JF  - e&i Elektrotechnik und Informationstechnik
KW  - Semantics
KW  - Production Process
KW  - Innovation
KW  - Agriculture
Y1  - 2019
ER  - 
TY  - JOUR
A1  - Wöber, Wilfried
A1  - Mehnen, Lars
A1  - Curto, Manuel
A1  - Dias Tibihika, Papius
A1  - Tesfaye, Genanaw
A1  - Meimberg, Harald
T1  - Investigating Shape Variation Using Generalized Procrustes Analysis and Machine Learning
JF  - Applied Sciences
N2  - Abstract: The biological investigation of a population’s shape diversity using digital images is typi-
cally reliant on geometrical morphometrics, which is an approach based on user-defined landmarks.
In contrast to this traditional approach, the progress in deep learning has led to numerous applications
ranging from specimen identification to object detection. Typically, these models tend to become black
boxes, which limits the usage of recent deep learning models for biological applications. However, the
progress in explainable artificial intelligence tries to overcome this limitation. This study compares
the explanatory power of unsupervised machine learning models to traditional landmark-based
approaches for population structure investigation. We apply convolutional autoencoders as well
as Gaussian process latent variable models to two Nile tilapia datasets to investigate the latent
structure using consensus clustering. The explanatory factors of the machine learning models were
extracted and compared to generalized Procrustes analysis. Hypotheses based on the Bayes factor are
formulated to test the unambiguity of population diversity unveiled by the machine learning models.
The findings show that it is possible to obtain biologically meaningful results relying on unsupervised
machine learning. Furthermore we show that the machine learning models unveil latent structures
close to the true population clusters. We found that 80% of the true population clusters relying on
the convolutional autoencoder are significantly different to the remaining clusters. Similarly, 60% of
the true population clusters relying on the Gaussian process latent variable model are significantly
different. We conclude that the machine learning models outperform generalized Procrustes analysis,
where 16% of the population cluster was found to be significantly different. However, the applied
machine learning models still have limited biological explainability. We recommend further in-depth
investigations to unveil the explanatory factors in the used model.

Keywords: generalized procrustes analysis; machine learning; convolutional autoencoder; Gaussian
process latent variable models
KW  - generalized procrustes analysis
KW  - machine learning
KW  - convolutional autoencoder
KW  - Gaussian process latent variable models
Y1  - 
VL  - 2022
IS  - 12(6), 3158
ER  - 
TY  - JOUR
A1  - Wöber, Wilfried
A1  - Curto, Manuel
A1  - Tibihika, Papius D.
A1  - Meulenboek, Paul
A1  - Alemayehu, Esayas
A1  - Mehnen, Lars
A1  - Meimberg, Harald
A1  - Sykacek, Peter
T1  - Identifying geographically differentiated features of Ethopian Nile tilapia (Oreochromis niloticus) morphology with machine learning
JF  - PlosONE
KW  - Machine Learning
Y1  - 
VL  - 16
IS  - 4
ER  - 
TY  - CHAP
A1  - Wöber, Wilfried
A1  - Tibihika, Papius D
A1  - Olaverri-Monreal, Cristina
A1  - Mehnen, Lars
A1  - Sykacek, Peter
A1  - Meimberg, Harald
T1  - Comparison of Unsupervised Learning Methods for Natural Image Processing
T2  - Biodiversity Information Science and Standards
KW  - Machine Learning
KW  - Deep Learning
KW  - Image Processing
Y1  - 
IS  - 3
ER  - 
TY  - CHAP
A1  - Wöber, Wilfried
A1  - Szuegyi, Daniel
A1  - Kubinger, Wilfried
A1  - Mehnen, Lars
T1  - A principal component analysis based object detection for thermal infra-red images
T2  - Proceedings of the 55th International Symposium ELMAR
KW  - Principal Component Analysis
KW  - Object Detection
KW  - Infra-Red Camera
Y1  - 2019
ER  -