Automatisierte Analyse von Impedanzspektren mittels konstruktivistischen maschinellen Lernens

  • O. Brookes*, M. Kukushkin*, M. Mirmehdi, C. Stephens, P. Dieguez, T. C. Hicks, S. Jones, K. Lee, M. S. McCarthy, A. Meier, E. Normand, E. G. Wessling, R. M.Wittig, K. Langergraber, K. Zuberbühler, L. Boesch, T. Schmid, M. Arandjelovic, H. Kühl, T. Burghardt, * - equal technical contribution
    The PanAf-FGBG Dataset: Understanding the Impact of Backgrounds in Wildlife Behaviour Recognition | LINK

    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville (USA), 11-15 June 2025

    Project page

  • J. Fiedler, M. Kukushkin, K.R. Kuckelsberg, J.L. Storck, M. Bogdan, T. Schmid, R. Kaschuba
    Optimization of the purity analysis of rapeseed by using hyperspectral imaging in the spectral range from 400 to 1600 nm | LINK

    Proceedings of Photonic Technologies in Plant and Agricultural Science II, SPIE, 2025

  • M. Kukushkin, M. Bogdan, T. Schmid
    BiCAE – A Bimodal Convolutional Autoencoder for Seed Purity Testing | LINK

    Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 9-13 September 2024, Vilnius (Lithuania)

  • F. Erichsmeier, M. Kukushkin, J. Fiedler, M. Enders, S. Goertz, M. Bogdan, T. Schmid, R. Kaschuba
    Automating the purity analysis of oilseed rape through usage of hyperspectral imaging | LINK

    Proceedings of Photonic Technologies in Plant and Agricultural Science, SPIE, 2024

  • V. Sophie Adama, Benjamin Schindler, Thomas Schmid
    Using Time Domain and Pearson’s Correlation to Predict Attention Focus in Autistic Spectrum Disorder from EEG P300 Components | LINK

    Proceedings of the XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. IFMBE Proceedings Vol. 76. Springer, S. 1890-1893, 2019

  • T. Schmid
    Automatisierte Analyse von Impedanzspektren mittels konstruktivistischen maschinellen Lernens | LINK

    Dissertation, Leipzig, 2018

  • T. Schmid, D. Günzel, M. Bogdan
    Automated Quantification of the Resistance of Epithelial Cell Layers from an Impedance Spectrum | LINK

    Proceedings of the Tenth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies, pp. 8-13, 2018

  • R. M. Fancy, L. Wang, T. Schmid, Q. Zeng, H. Wang, T. Zhou, D. J. Buchsbaum, Y. Song
    Characterization of the Interactions between Calmodulin and Death Receptor 5 in Triple-negative and Estrogen Receptor-positive Breast Cancer Cells: An Integrated Experimental and Computational Study | LINK

    The Journal of Biological Chemistry 291(24):12862-70, 2016

  • Thomas Schmid
    Forschungsorientierte Reflexion von Primärliteratur für Master-Studierende der Informatik und Bioinformatik | LINK

    HDS.Journal – Werkstattberichte : Lehr-Lern-Projekte, 2015/2, S. 46-52

  • T. Schmid, D. Günzel, M. Bogdan
    Automated Quantification of the Capacitance of Epithelial Cell Layers from an Impedance Spectrum | LINK

    Proceedings of the Seventh International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies, pp. 27-32, 2015

  • Thomas Schmid
    Macht „Big Data“ synthetische Datensätze überflüssig? | LINK

    Lecture Notes in Informatics S-13, S. 61-64, 2014

  • T. Schmid, D. Günzel, M. Bogdan
    Automated Quantification of the Relation between Resistor-Capacitor Subcircuits from an Impedance Spectrum | LINK

    Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, pp. 141-148, 2014

  • T. Schmid, M. Bogdan, D. Günzel
    Discerning Apical and Basolateral Properties of HT-29/B6 and IPEC-J2 Cell Layers by Impedance Spectroscopy, Mathematical Modeling and Machine Learning | LINK

    PLoS ONE 8(7): e62913, 2013

  • Thomas Schmid
    Wie man zwischen den Zahlen liest. Data-Mining und computergestützte Vorhersagen am Beispiel Bioinformatik | LINK

    Arbeitstitel – Forum für Leipziger Promovierende 5(1), S. 13-29, 2013

  • T. Schmid, D. Günzel, M. Bogdan
    Efficient prediction of x-axis intercepts of discrete impedance spectra | LINK

    Proceedings of the 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), p. 185-190, 2013

  • Dorothee Günzel, Silke S. Zakrzewski, Thomas Schmid, Maria Pangalos, John Wiedenhoeft, Corinna Blasse, Christopher Ozboda, Susanne M. Krug
    From TER to trans- and paracellular resistance: lessons from impedance spectroscopy | LINK

    Annals of the New York Academy of Sciences 1257, S. 142-151, 2012

  • T. Schmid, D. Günzel, M. Bogdan
    Using an artificial neural network to determine electrical properties of epithelia

    ICANN, Thessaloniki, LNCS vol. 6352, pp. 211-216, 2010