Statistical and neural methods for vision-based analysis of facial expressions and gender. - Torsten Wilhelm; Hans-Joachim Böhme; Horst-Michael Gross; Andreas Backhaus (SMC (3), 2004)

Contextual Learning in the Selective Attention for Identification model (CL-SAIM): Modeling contextual cueing in visual search tasks. - Andreas Backhaus; Dietmar Heinke; Glyn W. Humphreys (CVPR Workshops, 2005)

The Selective Attention for Identification Model (SAIM): Simulating Visual Search in Natural Colour Images. - Dietmar Heinke; Andreas Backhaus; Yaoru Sun; Glyn W. Humphreys (WAPCV, 2007)

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

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)

Modelling Visual Search with the Selective Attention for Identification Model (VS-SAIM): A Novel Explanation for Visual Search Asymmetries. - Dietmar Heinke; Andreas Backhaus (Cogn. Comput., 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)

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)

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)

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)

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)

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)

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)

Optimal multispectral sensor configurations through machine learning for cognitive agriculture. - Florian Becker; Andreas Backhaus; Felix Johrden; Merle Flitter (Autom., 2021)

A new framework for calibrating COVID-19 SEIR models with spatial-/time-varying coefficients using genetic and sliding window algorithms. - Huan Zhou 005; Ralf Schneider; Sebastian Klüsener; Andreas Backhaus (CoRR, 2024)