@article{KaniusasPfuetznerMehnen,
  author    = {Kaniusas, Eugenijus and Pf{\"u}tzner, Helmut and Mehnen, Lars},
  title     = {Optical tissue absorption sensor on the thorax: Possibilities and restrictions},
  series = {International Journal of Applied Electromagnetics and Mechanics},
  volume    = {25},
  journal   = {International Journal of Applied Electromagnetics and Mechanics},
  number    = {1-4},
  pages     = {649 -- 655},
  subject      = {Tissue Absorption},
  language  = {en}
}
@article{WoeberMehnenCurtoetal.,
  author    = {W{\"o}ber, Wilfried and Mehnen, Lars and Curto, Manuel and Dias Tibihika, Papius and Tesfaye, Genanaw and Meimberg, Harald},
  title     = {Investigating Shape Variation Using Generalized Procrustes Analysis and Machine Learning},
  series = {Applied Sciences},
  volume    = {2022},
  journal   = {Applied Sciences},
  number    = {12(6), 3158},
  pages     = {26},
  abstract  = {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},
  subject      = {generalized procrustes analysis},
  language  = {en}
}
@article{KaniusasPfuetznerMehnenetal.,
  author    = {Kaniusas, Eugenijus and Pf{\"u}tzner, Helmut and Mehnen, Lars and Kosel, J{\"u}rgen and Meydan, Turgut and Vazquez, Manuel and Rohn, Michael and Merlo, Alberto Maria and Marquardt, Bernd},
  title     = {Dynamic Measuring of Inductivity Changes by Adaptive Controlling and Lock-in Technique},
  series = {Journal of Electrical Engineering},
  volume    = {2004},
  journal   = {Journal of Electrical Engineering},
  number    = {55 / 10},
  pages     = {49 -- 52},
  subject      = {Adaptive Controlling},
  language  = {en}
}
@article{PfuetznerKaniusasMehnenetal.,
  author    = {Pf{\"u}tzner, Helmut and Kaniusas, Eugenijus and Mehnen, Lars and Meydan, Turgut and Vazquez, Manuel and Rohn, Michael and Merlo, Alberto and Marquardt, Bernd},
  title     = {Magnetorestrictive bilayers for multi-functional sensor families},
  series = {Sensors and Actuators A},
  volume    = {129},
  journal   = {Sensors and Actuators A},
  number    = {1},
  pages     = {154 -- 158},
  subject      = {Magnetism},
  language  = {en}
}
@article{ObergruberMehnen,
  author    = {Obergruber, Julian and Mehnen, Lars},
  title     = {Development of a paraglide control system for automatic pitch},
  series = {Proceedings of the 11th Conference of the International Sports Engineering Association (ISEA) 2016},
  journal   = {Proceedings of the 11th Conference of the International Sports Engineering Association (ISEA) 2016},
  subject      = {Control System},
  language  = {de}
}
@article{KaniusasMehnenPfuetzner,
  author    = {Kaniusas, Eugenijus and Mehnen, Lars and Pf{\"u}tzner, Helmut},
  title     = {Magnetostrictive amorphous bilayers and trilayers for thermal sensors},
  series = {Journal of Magnetism and Magnetic Materials},
  journal   = {Journal of Magnetism and Magnetic Materials},
  number    = {254 - 255},
  pages     = {624 -- 626},
  subject      = {Magnetism},
  language  = {en}
}
@article{WoeberCurtoTibihikaetal.,
  author    = {W{\"o}ber, Wilfried and Curto, Manuel and Tibihika, Papius D. and Meulenboek, Paul and Alemayehu, Esayas and Mehnen, Lars and Meimberg, Harald and Sykacek, Peter},
  title     = {Identifying geographically differentiated features of Ethopian Nile tilapia (Oreochromis niloticus) morphology with machine learning},
  series = {PlosONE},
  volume    = {16},
  journal   = {PlosONE},
  number    = {4},
  subject      = {Machine Learning},
  language  = {en}
}
@article{KaniusasPfuetznerMehnenetal.,
  author    = {Kaniusas, Eugenijus and Pf{\"u}tzner, Helmut and Mehnen, Lars and Kosel, J{\"u}rgen and Hasenzagl, Andreas},
  title     = {Optimisation of Magnetostrictive Bilayer Sensors for Medical Applications},
  series = {International Journal of Applied Electromagnetics and Mechanics},
  volume    = {28},
  journal   = {International Journal of Applied Electromagnetics and Mechanics},
  number    = {1,2},
  pages     = {193 -- 199},
  subject      = {Magnetism},
  language  = {en}
}
@article{KaniusasPfuetznerMehnenetal.,
  author    = {Kaniusas, Eugenijus and Pf{\"u}tzner, Helmut and Mehnen, Lars and Kosel, J{\"u}rgen and Varoneckas, Giedrius and Alonderis, Audrius and Meydan, Turgut and Vazquez, Manuel and Rohn, Michael and Merlo, Alberto and Marquardt, Bernd},
  title     = {Magnetoelastic bilayer concept for skin curvature sensor},
  series = {Ultrasound},
  volume    = {52},
  journal   = {Ultrasound},
  number    = {3},
  pages     = {42 -- 46},
  subject      = {Magnetism},
  language  = {en}
}
@article{KaniusasPfuetznerMehnenetal.,
  author    = {Kaniusas, Eugenijus and Pf{\"u}tzner, Helmut and Mehnen, Lars and Kosel, J{\"u}rgen and Tellez-Blanco, Juan C. and Varoneckas, Giedrius and Alonderis, Audrius and Meydan, Turgut and Vazquez, Manuel and Rohn, Michael and Merlo, Alberto and Marquardt, Bernd},
  title     = {Method for continuous non-disturbing monitoring of blood pressure by magnetoelastic skin curvature sensor and ECG},
  series = {IEEE Sensors Journal},
  volume    = {6},
  journal   = {IEEE Sensors Journal},
  number    = {3},
  pages     = {819 -- 828},
  subject      = {Blood Pressure},
  language  = {en}
}