Self-organizing ANNs for planetary surface composition research. - Erzsébet Merényi (ESANN, 1998)

Hyper-Spectral Satellite Images: Interval Methods May Be Helpful. - Erzsébet Merényi; Scott A. Starks; Karen Villaverde (Reliab. Comput., 1998)

Estimating the intrinsic dimensionality of hyperspectral images. - Jörg Bruske; Erzsébet Merényi (ESANN, 1999)

The challenges in spectral image analysis: an introduction, and review of ANN approaches. - Erzsébet Merényi (ESANN, 1999)

Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit. - Donald MacDonald; Emilio Corchado; Colin Fyfe; Erzsébet Merényi (ICANN, 2002)

Neural maps in remote sensing image analysis. - Thomas Villmann; Erzsébet Merényi; Barbara Hammer (Neural Networks, 2003)

Forbidden Magnification? I. - Abha Jain; Erzsébet Merényi (ESANN, 2004)

Forbidden magnification? II. - Erzsébet Merényi; Abha Jain (ESANN, 2004)

Mapping Surface Materials on Mars from Mars Pathfinder Spectral Images with HYPEREYE. - Erzsébet Merényi; William H. Farrand; Philip Tracadas (ITCC (2), 2004)

Data topology visualization for the Self-Organizing Map. - Kadim Tasdemir; Erzsébet Merényi (ESANN, 2006)

Weighted differential topographic function: a refinement of topographic function. - Lili Zhang; Erzsébet Merényi (ESANN, 2006)

Fuzzy Labeled Self-Organizing Map for Classification of Spectra. - Thomas Villmann; Frank-Michael Schleif; Erzsébet Merényi; Barbara Hammer (IWANN, 2007)

Min(d)ing the small details: discovery of critical knowledge through precision manifold learning, and application to onboard decision support. - Erzsébet Merényi; Lili Zhang; Kadim Tasdemir (SoSE, 2007)

Advances in computational intelligence and learning. - Michael Biehl; Erzsébet Merényi; Fabrice Rossi (Neurocomputing, 2007)

Explicit Magnification Control of Self-Organizing Maps for "Forbidden" Data. - Erzsébet Merényi; Abha Jain; Thomas Villmann (IEEE Trans. Neural Networks, 2007)

Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization. - Kadim Tasdemir; Erzsébet Merényi (Discovery Science, 2008)

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

Relevance-Based Feature Extraction for Hyperspectral Images. - Michael J. Mendenhall; Erzsébet Merényi (IEEE Trans. Neural Networks, 2008)

Learning Highly Structured Manifolds: Harnessing the Power of SOMs. - Erzsébet Merényi; Kadim Tasdemir; Lili Zhang (Similarity-Based Clustering, 2009)

Automated labeling of segmented hyperspectral imagery via spectral matching. - Brian D. Bue; Erzsébet Merényi; Beáta Csathó (WHISPERS, 2009)

Minimum Surface Bhattacharyya feature selection. - Jose Andres Gonzalez; Michael J. Mendenhall; Erzsébet Merényi (WHISPERS, 2009)

On the evaluation of synthetic hyperspectral imagery. - Michael J. Mendenhall; Erzsébet Merényi (WHISPERS, 2009)

A novel scheme for the compression and classification of hyperspectral images. - Bei Xie; Tamal Bose; Erzsébet Merényi (WHISPERS, 2009)

An SOM-Hybrid Supervised Model for the Prediction of Underlying Physical Parameters from Near-Infrared Planetary Spectra. - Lili Zhang; Erzsébet Merényi; William M. Grundy; Eliot F. Young (WSOM, 2009)

Exploiting Data Topology in Visualization and Clustering of Self-Organizing Maps. - Kadim Tasdemir; Erzsébet Merényi (IEEE Trans. Neural Networks, 2009)

Learning Multiple Latent Variables with Self-Organizing Maps. - Lili Zhang; Erzsébet Merényi (GrC, 2010)

Using spatial correspondences for hyperspectral knowledge transfer: Evaluation on synthetic data. - Brian D. Bue; Erzsébet Merényi (WHISPERS, 2010)

Automated Labeling of Materials in Hyperspectral Imagery. - Brian D. Bue; Erzsébet Merényi; Beáta Csathó (IEEE Trans. Geosci. Remote. Sens., 2010)

An evaluation of class knowledge transfer from synthetic to real hyperspectral imagery. - Brian D. Bue; Erzsébet Merényi; Beáta Csathó (WHISPERS, 2011)

Learning in the context of very high dimensional data (Dagstuhl Seminar 11341). - Michael Biehl; Barbara Hammer; Erzsébet Merényi; Alessandro Sperduti; Thomas Villmann (Dagstuhl Reports, 2011)

A Validity Index for Prototype-Based Clustering of Data Sets With Complex Cluster Structures. - Kadim Tasdemir; Erzsébet Merényi (IEEE Trans. Syst. Man Cybern. Part B, 2011)

gNBXe - a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps. - Jan Lachmair; Erzsébet Merényi; Mario Porrmann; Ulrich Rückert 001 (ESANN, 2012)

Parallel neural hardware: the time is right. - Ulrich Rückert 001; Erzsébet Merényi (ESANN, 2012)

Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps. - Thomas Villmann; Erzsébet Merényi; William H. Farrand (ESANN, 2012)

A reconfigurable neuroprocessor for self-organizing feature maps. - Jan Lachmair; Erzsébet Merényi; Mario Porrmann; Ulrich Rückert 001 (Neurocomputing, 2013)

An Adaptive Similarity Measure for Classification of Hyperspectral Signatures. - Brian D. Bue; Erzsébet Merényi (IEEE Geosci. Remote. Sens. Lett., 2013)

SOM and MCODE methods of defining functional clusters in MRI of the brain. - Patrick O'Driscoll; Erzsébet Merényi; Christof Karmonik; Robert G. Grossman (EMBC, 2014)

The Sky Is Not the Limit. - Erzsébet Merényi (WSOM, 2014)

Classification of hyperspectral imagery with neural networks: comparison to conventional tools. - Erzsébet Merényi; William H. Farrand; James V. Taranik; Timothy B. Minor (EURASIP J. Adv. Signal Process., 2014)

Foreword to the Special Issue on Machine Learning for Remote Sensing Data Processing. - Devis Tuia; Erzsébet Merényi; Xiuping Jia; Manuel Graña Romay (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Deep data: discovery and visualization Application to hyperspectral ALMA imagery. - Erzsébet Merényi; Joshua Taylor; Andrea Isella (Astroinformatics, 2016)

Mining complex hyperspectral ALMA cubes for structure with neural machine learning. - Erzsébet Merényi; Joshua Taylor; Andrea Isella (SSCI, 2016)

The Effect of SOM Size and Similarity Measure on Identification of Functional and Anatomical Regions in fMRI Data. - Patrick O'Driscoll; Erzsébet Merényi; Christof Karmonik; Robert G. Grossman (WSOM, 2016)

SOM-empowered graph segmentation for fast automatic clustering of large and complex data. - Erzsébet Merényi; Joshua Taylor (WSOM, 2017)

Using spatial characteristics to aid automation of SOM segmentation of functional image data. - Patrick O'Driscoll; Erzsébet Merényi; Robert G. Grossman (WSOM, 2017)

A Probabilistic Method for Pruning CADJ Graphs with Applications to SOM Clustering. - Joshua Taylor; Erzsébet Merényi (WSOM+, 2019)

Empowering graph segmentation methods with SOMs and CONN similarity for clustering large and complex data. - Erzsébet Merényi; Joshua Taylor (Neural Comput. Appl., 2020)

A Parameterless t-SNE for Faithful Cluster Embeddings from Prototype-based Learning and CONN Similarity. - Joshua Taylor; Erzsébet Merényi (ESANN, 2021)

Automating t-SNE parameterization with prototype-based learning of manifold connectivity. - Joshua Taylor; Erzsébet Merényi (Neurocomputing, 2022)

DM-pruning CADJ graphs for SOM clustering. - Joshua Taylor; Erzsébet Merényi (Neural Comput. Appl., 2022)

SOM-based Classification and a Novel Stopping Criterion for Astroparticle Applications. - Luis Sanchez; Erzsébet Merényi; Christopher D. Tunnell (ESANN, 2023)