Three-dimensional Self-Organizing Maps for Classification of Image Properties. - Udo Seiffert; Bernd Michaelis (ANNES, 1995)

Adaptive three-dimensional self-organizing map with a two-dimensional input layer. - Udo Seiffert; Bernd Michaelis (ANZIIS, 1996)

Rekonstruktion und Klassifikation dendritischer Spines aus konfokalen Bilddaten. - Andreas Herzog; G. Sommerkorn; Udo Seiffert; Bernd Michaelis; Katharina Braun; Werner Zuschratter (Bildverarbeitung für die Medizin, 1996)

Adaptive filtering of distorted displacement vector fields using artificial neural networks. - Bernd Michaelis; Olaf Schnelting; Udo Seiffert; Rüdiger Mecke (ICPR, 1996)

Classification of 3-D Dendritic Spines using Self-Organizing Maps. - G. Sommerkorn; Udo Seiffert; D. Surmeli; Andreas Herzog; Bernd Michaelis; Katharina Braun (ICANNGA, 1997)

Growing 3D-SOMs with 2D-Input Layer as a Classification Tool in a Motion Detection System. - Udo Seiffert; Bernd Michaelis (Int. J. Neural Syst., 1997)

Estimating Motion Parameters with Three-Dimensional Self-Organizing Maps. - Udo Seiffert; Bernd Michaelis (Inf. Sci., 1997)

Wachsende mehrdimensionale selbstorganisierende Karten zur Analyse bewegter Szenen. - Udo Seiffert (1998)

Indirect Unsuperivised Training of Backpropagation Nets. - Udo Seiffert; Bernd Michaelis (SIP, 1999)

Multiple Layer Perceptron training using genetic algorithms. - Udo Seiffert (ESANN, 2001)

Neural Techniques in Logo Recognition. - Vaijayanti Joshi; Lakhmi C. Jain; Udo Seiffert; Kathleen Zyga; Richard Price; Friedrich Leisch (HIS, 2001)

Multi-Dimensional Self-Organizing Maps on Massively Parallel Hardware. - Udo Seiffert; Bernd Michaelis (WSOM, 2001)

Improving Still Image Coding by an SOM-Controlled Associative Memory. - Gerald Krell; R. Rebmann; Udo Seiffert; Bernd Michaelis (CIARP, 2003)

Associative Correction Of Compression Artefacts With A Self-Organizing Map Classifying The Image Content. - R. Rebmann; Gerald Krell; Udo Seiffert; Bernd Michaelis (DCC, 2003)

Digital Image Processing with Neural Networks. - Axel Wismüller; Udo Seiffert (ESANN, 2003)

Biologically Inspired Image Compression in Biomedical High-Throughput Screening. - Udo Seiffert (BioADIT, 2004)

Automating Microscope Colour Image Analysis Using the Expectation Maximisation Algorithm. - Alexander Ihlow; Udo Seiffert (DAGM-Symposium, 2004)

Theory and applications of neural maps. - Thomas Villmann; Udo Seiffert; Axel Wismüller (ESANN, 2004)

Haustoria Segmentation in Microscope Colour Images of Barley Cells. - Alexander Ihlow; Udo Seiffert (Workshop Farbbildverarbeitung, 2004)

Improving Image Processing Systems by Artificial Neural Networks. - R. Rebmann; Bernd Michaelis; Gerald Krell; Udo Seiffert; F. Püschel (Reading and Learning, 2004)

Artificial neural networks on massively parallel computer hardware. - Udo Seiffert (Neurocomputing, 2004)

Adaptive Implementation of Artificial Neural Networks Reflecting Changing Hardware Resources at Run-Time. - Udo Seiffert (Artificial Intelligence and Applications, 2005)

Generalized Relevance LVQ with Correlation Measures for Biological Data. - Marc Strickert; Nese Sreenivasulu; Winfriede Weschke; Udo Seiffert; Thomas Villmann (ESANN, 2005)

High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data. - Marc Strickert; Stefan Teichmann; Nese Sreenivasulu; Udo Seiffert (ICANN (1), 2005)

Adaptive Feature Selection for Classification of Microscope Images. - Ralf Tautenhahn; Alexander Ihlow; Udo Seiffert (WILF, 2005)

Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data. - Marc Strickert; Nese Sreenivasulu; Silke Peterek; Winfriede Weschke; Hans-Peter Mock; Udo Seiffert (ANNPR, 2006)

Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. - Thomas Villmann; Udo Seiffert; Frank-Michael Schleif; Cornelia Brüß; Tina Geweniger; Barbara Hammer (ANNPR, 2006)

Towards Automatic Segmentation of Serial High-Resolution Images. - Cornelia Brüß; Marc Strickert; Udo Seiffert (Bildverarbeitung für die Medizin, 2006)

Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. - Thomas Villmann; Barbara Hammer; Udo Seiffert (BioADIT, 2006)

Fuzzy image segmentation with Fuzzy Labelled Neural Gas. - Cornelia Brüß; Felix Bollenbeck; Frank-Michael Schleif; Winfriede Weschke; Thomas Villmann; Udo Seiffert (ESANN, 2006)

Neural networks and machine learning in bioinformatics - theory and applications. - Udo Seiffert; Barbara Hammer; Samuel Kaski; Thomas Villmann (ESANN, 2006)

Sanger-driven MDSLocalize - a comparative study for genomic data. - Marc Strickert; Nese Sreenivasulu; Udo Seiffert (ESANN, 2006)

Training of Large-Scale Feed-Forward Neural Networks. - Udo Seiffert (IJCNN, 2006)

Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis. - Marc Strickert; Udo Seiffert; Nese Sreenivasulu; Winfriede Weschke; Thomas Villmann; Barbara Hammer (Neurocomputing, 2006)

Correlation-based Data Representation. - Marc Strickert; Udo Seiffert (Similarity-based Clustering and its Application to Medicine and Biology, 2007)

Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. - Thomas Villmann; Marc Strickert; Cornelia Brüß; Frank-Michael Schleif; Udo Seiffert (ESANN, 2007)

Intuitive Clustering of Biological Data. - Barbara Hammer; Alexander Hasenfuss; Frank-Michael Schleif; Thomas Villmann; Marc Strickert; Udo Seiffert (IJCNN, 2007)

Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue. - Marc Strickert; Nese Sreenivasulu; Björn Usadel; Udo Seiffert (BMC Bioinform., 2007)

Towards Automatic Generation of 3D Models of Biological Objects Based on Serial Sections. - Vincent Jasper Dercksen; Cornelia Brüß; Detlev Stalling; Sabine Gubatz; Udo Seiffert; Hans-Christian Hege (Visualization in Medicine and Life Sciences, 2008)

Machine learning approches and pattern recognition for spectral data. - Thomas Villmann; Erzsébet Merényi; Udo Seiffert (ESANN, 2008)

Fuzzy image segmentation by potential fields. - Udo Seiffert; Felix Bollenbeck (FUZZ-IEEE, 2008)

Fast registration-based automatic segmentation of serial section images for high-resolution 3-D plant seed modeling. - Felix Bollenbeck; Udo Seiffert (ISBI, 2008)

4D Warping for Analysing Morphological Changes in Seed Development of Barley Grains. - Rainer Pielot; Udo Seiffert; Bertram Manz; Diana Weier; Frank Volke; Winfriede Weschke (VISAPP (1), 2008)

Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. - Marc Strickert; Frank-Michael Schleif; Udo Seiffert; Thomas Villmann (Inteligencia Artif., 2008)

Three-Dimensional Multimodality Modelling by Integration of High-Resolution Interindividual Atlases and Functional MALDI-IMS Data. - Felix Bollenbeck; Stephanie Kaspar; Hans-Peter Mock; Diana Weier; Udo Seiffert (BICoB, 2009)

Inter-modality registration of NMRi and histological section images using neural networks regression in Gabor feature space. - Felix Bollenbeck; Rainer Pielot; Diana Weier; Winfriede Weschke; Udo Seiffert (CIIP, 2009)

Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. - Marc Strickert; Frank-Michael Schleif; Thomas Villmann; Udo Seiffert (Similarity-Based Clustering, 2009)

Remote Rendering of Large Biological Datasets. - Wolfram Schoor; Rüdiger Mecke; Udo Seiffert; Felix Bollenbeck; Uwe Scholz (GRAPP, 2009)

From Individual Intensity Voxel Data to Inter-individual Probabilistic Atlases of Biological Objects by an Interleaved Registration-segmentation Approach. - Felix Bollenbeck; Diana Weier; Wolfram Schoor; Udo Seiffert (VISAPP (1), 2009)

Multimodal Registration of NMR-volumes and Histological Cross-sections of Barley Grains on the Cell Broadband Engine Processor. - Rainer Pielot; Udo Seiffert; Bertram Manz; Diana Weier; Frank Volke; Falk Schreiber; Winfriede Weschke (VISAPP (1), 2009)

VR Based Visualization and Exploration of Plant Biological Data. - Wolfram Schoor; Felix Bollenbeck; Thomas Seidl 002; Diana Weier; Winfriede Weschke; Bernhard Preim; Udo Seiffert; Rüdiger Mecke (J. Virtual Real. Broadcast., 2009)

Computational Intelligence in Biomedical Image Processing. - Felix Bollenbeck; Udo Seiffert (Foundations of Computational Intelligence (5), 2009)

Validation of unsupervised clustering methods for leaf phenotype screening. - Andreas Backhaus; Asuka Kuwabara; Andrew Fleming; Udo Seiffert (ESANN, 2010)

Joint Registration and Segmentation of Histological Volume Data by Diffusion-Based Label Adaption. - Felix Bollenbeck; Udo Seiffert (ICPR, 2010)

Clustering of crop phenotypes by means of hyperspectral signatures using artificial neural networks. - Udo Seiffert; Felix Bollenbeck; Hans-Peter Mock; Andrea Matros (WHISPERS, 2010)

Recent trends in computational intelligence in life sciences. - Udo Seiffert; Frank-Michael Schleif; Dietlind Zühlke (ESANN, 2011)

Robust classification of the nutrition state in crop plants by hyperspectral imaging and artificial neural networks. - Andreas Backhaus; Felix Bollenbeck; Udo Seiffert (WHISPERS, 2011)

A multivariate wavelet-PCA denoising-filter for hyperspectral images. - Felix Bollenbeck; Andreas Backhaus; Udo Seiffert (WHISPERS, 2011)

Relevance Learning in Unsupervised Vector Quantization Based on Divergences. - Marika Kästner; Andreas Backhaus; Tina Geweniger; Sven Haase; Udo Seiffert; Thomas Villmann (WSOM, 2011)

Classifying Scotch Whisky from near-infrared Raman spectra with a Radial Basis Function Network with Relevance Learning. - Andreas Backhaus; Praveen Cheriyan Ashok; Bavishna Balagopal Praveen; Kishan Dholakia; Udo Seiffert (ESANN, 2012)

Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting. - Andreas Backhaus; Jan Lachmair; Ulrich Rückert 001; Udo Seiffert (ESANN, 2012)

Fractal analysis of resting state functional connectivity of the brain. - Wonsang You; Sophie Achard; Jörg Stadler; Bernd Brückner; Udo Seiffert (IJCNN, 2012)

Quantitative Measurements of model interpretability for the analysis of spectral data. - Andreas Backhaus; Udo Seiffert (CIDM, 2013)

Processing Hyperspectral Data in Machine Learning. - Thomas Villmann; Marika Kästner; Andreas Backhaus; Udo Seiffert (ESANN, 2013)

A comparison of late fusion methods for object detection. - Uwe Knauer; Udo Seiffert (ICIP, 2013)

Cascaded Reduction and Growing of Result Sets for Combining Object Detectors. - Uwe Knauer; Udo Seiffert (MCS, 2013)

Fast image segmentation based on boosted random forests, integral images, and features on demand. - Uwe Knauer; Udo Seiffert (CIEL, 2014)

Beyond Standard Metrics - On the Selection and Combination of Distance Metrics for an Improved Classification of Hyperspectral Data. - Uwe Knauer; Andreas Backhaus; Udo Seiffert (WSOM, 2014)

Classification in high-dimensional spectral data: Accuracy vs. interpretability vs. model size. - Andreas Backhaus; Udo Seiffert (Neurocomputing, 2014)

ANNIE - Artificial Neural Network-based Image Encoder. - Udo Seiffert (Neurocomputing, 2014)

Evaluation of Fusion Methods for Gamma-Divergence-Based Neural Network Ensembles. - Uwe Knauer; Andreas Backhaus; Udo Seiffert (SSCI, 2015)

Fusion trees for fast and accurate classification of hyperspectral data with ensembles of γ-divergence-based RBF networks. - Uwe Knauer; Andreas Backhaus; Udo Seiffert (Neural Comput. Appl., 2015)

Functional Representation of Prototypes in LVQ and Relevance Learning. - Friedrich Melchert; Udo Seiffert; Michael Biehl (WSOM, 2016)

Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities. - Marika Kaden; David Nebel; Friedrich Melchert; Andreas Backhaus; Udo Seiffert; Thomas Villmann (WSOM, 2017)

Prototypes and matrix relevance learning in complex fourier space. - Michiel Straat; Marika Kaden; Matthias Gay; Thomas Villmann; Alexander Lampe; Udo Seiffert; Michael Biehl; Friedrich Melchert (WSOM, 2017)

Phenoliner: A New Field Phenotyping Platform for Grapevine Research. - Anna Kicherer; Katja Herzog; Nele Bendel; Hans-Christian Klück; Andreas Backhaus; Markus Wieland; Johann Christian Rose; Lasse Klingbeil; Thomas Läbe; Christian Hohl; Willi Petry; Heiner Kuhlmann; et al. (Sensors, 2017)

Transfer Learning for transferring machine-learning based models among hyperspectral sensors. - Patrick Menz; Andreas Backhaus; Udo Seiffert (ESANN, 2019)

Tree Species Classification Based on Hybrid Ensembles of a Convolutional Neural Network (CNN) and Random Forest Classifiers. - Uwe Knauer; Cornelius Styp von Rekowski; Marianne Stecklina; Tilman Krokotsch; Tuan Pham Minh; Viola Hauffe; David Kilias; Ina Ehrhardt; Herbert Sagischewski; Sergej Chmara; Udo Seiffert (Remote. Sens., 2019)

Adaptive basis functions for prototype-based classification of functional data. - Friedrich Melchert; Gabriele Bani; Udo Seiffert; Michael Biehl (Neural Comput. Appl., 2020)

Learning vector quantization and relevances in complex coefficient space. - Michiel Straat; Marika Kaden; Matthias Gay; Thomas Villmann; Alexander Lampe; Udo Seiffert; Michael Biehl; Friedrich Melchert (Neural Comput. Appl., 2020)

Detection of Two Different Grapevine Yellows in Vitis vinifera Using Hyperspectral Imaging. - Nele Bendel; Andreas Backhaus; Anna Kicherer; Janine Köckerling; Michael Maixner; Barbara Jarausch; Sandra Biancu; Hans-Christian Klück; Udo Seiffert; Ralf T. Voegele; Reinhard Töpfer (Remote. Sens., 2020)

Detection of Grapevine Leafroll-Associated Virus 1 and 3 in White and Red Grapevine Cultivars Using Hyperspectral Imaging. - Nele Bendel; Anna Kicherer; Andreas Backhaus; Janine Köckerling; Michael Maixner; Elvira Bleser; Hans-Christian Klück; Udo Seiffert; Ralf T. Voegele; Reinhard Töpfer (Remote. Sens., 2020)

Evaluation of RGB and Multispectral Unmanned Aerial Vehicle (UAV) Imagery for High-Throughput Phenotyping and Yield Prediction in Barley Breeding. - Paul Herzig; Peter Borrmann; Uwe Knauer; Hans-Christian Klück; David Kilias; Udo Seiffert; Klaus Pillen; Andreas Maurer (Remote. Sens., 2021)

Federated learning vector quantization for dealing with drift between nodes. - Johannes Brinkrolf; Valerie Vaquet; Fabian Hinder; Patrick Menz; Udo Seiffert; Barbara Hammer (ESANN, 2022)

From hyperspectral to multispectral sensing - from simulation to reality: A comprehensive approach for calibration model transfer. - Patrick Menz; Valerie Vaquet; Barbara Hammer; Udo Seiffert (ESANN, 2022)

Investigating intensity and transversal drift in hyperspectral imaging data. - Valerie Vaquet; Patrick Menz; Udo Seiffert; Barbara Hammer (Neurocomputing, 2022)