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Erzsébet Merényi
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- affiliation: Rice University, Houston, USA
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2020 – today
- 2023
- [c35]Luis Sanchez, Erzsébet Merényi, Christopher D. Tunnell:
SOM-based Classification and a Novel Stopping Criterion for Astroparticle Applications. ESANN 2023 - 2022
- [j15]Joshua Taylor, Erzsébet Merényi:
Automating t-SNE parameterization with prototype-based learning of manifold connectivity. Neurocomputing 507: 441-452 (2022) - [j14]Joshua Taylor
, Erzsébet Merényi:
DM-pruning CADJ graphs for SOM clustering. Neural Comput. Appl. 34(1): 25-38 (2022) - 2021
- [c34]Joshua Taylor, Erzsébet Merényi:
A Parameterless t-SNE for Faithful Cluster Embeddings from Prototype-based Learning and CONN Similarity. ESANN 2021 - 2020
- [j13]Erzsébet Merényi
Empowering graph segmentation methods with SOMs and CONN similarity for clustering large and complex data. Neural Comput. Appl. 32(24): 18161-18178 (2020)
2010 – 2019
- 2019
- [c33]Joshua Taylor, Erzsébet Merényi:
A Probabilistic Method for Pruning CADJ Graphs with Applications to SOM Clustering. WSOM+ 2019: 44-54 - 2017
- [c32]Erzsébet Merényi, Joshua Taylor:
SOM-empowered graph segmentation for fast automatic clustering of large and complex data. WSOM 2017: 34-42 - [c31]Patrick O'Driscoll, Erzsébet Merényi, Robert G. Grossman:
Using spatial characteristics to aid automation of SOM segmentation of functional image data. WSOM 2017: 98-95 - 2016
- [c30]Erzsébet Merényi
Deep data: discovery and visualization Application to hyperspectral ALMA imagery. Astroinformatics 2016: 281-290 - [c29]Erzsébet Merényi, Joshua Taylor, Andrea Isella:
Mining complex hyperspectral ALMA cubes for structure with neural machine learning. SSCI 2016: 1-9 - [c28]Patrick O'Driscoll, Erzsébet Merényi, Christof Karmonik, Robert G. Grossman:
The Effect of SOM Size and Similarity Measure on Identification of Functional and Anatomical Regions in fMRI Data. WSOM 2016: 251-263 - [e1]Erzsébet Merényi, Michael J. Mendenhall, Patrick O'Driscoll:
Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016. Advances in Intelligent Systems and Computing 428, Springer 2016, ISBN 978-3-319-28517-7 [contents] - 2014
- [j12]Erzsébet Merényi, William H. Farrand, James V. Taranik, Timothy B. Minor:
Classification of hyperspectral imagery with neural networks: comparison to conventional tools. EURASIP J. Adv. Signal Process. 2014: 71 (2014) - [j11]Devis Tuia
Foreword to the Special Issue on Machine Learning for Remote Sensing Data Processing. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(4): 1007-1011 (2014) - [c27]Patrick O'Driscoll, Erzsébet Merényi, Christof Karmonik, Robert G. Grossman:
SOM and MCODE methods of defining functional clusters in MRI of the brain. EMBC 2014: 734-737 - [c26]Erzsébet Merényi:
The Sky Is Not the Limit. WSOM 2014: 181-186 - 2013
- [j10]Jan Lachmair, Erzsébet Merényi, Mario Porrmann
A reconfigurable neuroprocessor for self-organizing feature maps. Neurocomputing 112: 189-199 (2013) - [j9]Brian D. Bue, Erzsébet Merényi:
An Adaptive Similarity Measure for Classification of Hyperspectral Signatures. IEEE Geosci. Remote. Sens. Lett. 10(2): 381-385 (2013) - 2012
- [c25]Jan Lachmair, Erzsébet Merényi, Mario Porrmann, Ulrich Rückert:
gNBXe - a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps. ESANN 2012 - [c24]Ulrich Rückert, Erzsébet Merényi:
Parallel neural hardware: the time is right. ESANN 2012 - [c23]Thomas Villmann, Erzsébet Merényi, William H. Farrand:
Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps. ESANN 2012 - 2011
- [j8]Kadim Tasdemir
A Validity Index for Prototype-Based Clustering of Data Sets With Complex Cluster Structures. IEEE Trans. Syst. Man Cybern. Part B 41(4): 1039-1053 (2011) - [c22]Brian D. Bue, Erzsébet Merényi, Beáta Csathó:
An evaluation of class knowledge transfer from synthetic to real hyperspectral imagery. WHISPERS 2011: 1-4 - [i1]Michael Biehl
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341). Dagstuhl Reports 1(8): 67-95 (2011) - 2010
- [j7]Brian D. Bue, Erzsébet Merényi, Beáta Csathó:
Automated Labeling of Materials in Hyperspectral Imagery. IEEE Trans. Geosci. Remote. Sens. 48(11): 4059-4070 (2010) - [c21]Lili Zhang, Erzsébet Merényi:
Learning Multiple Latent Variables with Self-Organizing Maps. GrC 2010: 609-614 - [c20]Brian D. Bue, Erzsébet Merényi:
Using spatial correspondences for hyperspectral knowledge transfer: Evaluation on synthetic data. WHISPERS 2010: 1-4
2000 – 2009
- 2009
- [j6]Kadim Tasdemir
Exploiting Data Topology in Visualization and Clustering of Self-Organizing Maps. IEEE Trans. Neural Networks 20(4): 549-562 (2009) - [c19]Erzsébet Merényi, Kadim Tasdemir, Lili Zhang:
Learning Highly Structured Manifolds: Harnessing the Power of SOMs. Similarity-Based Clustering 2009: 138-168 - [c18]Brian D. Bue, Erzsébet Merényi, Beáta Csathó:
Automated labeling of segmented hyperspectral imagery via spectral matching. WHISPERS 2009: 1-4 - [c17]Jose Andres Gonzalez, Michael J. Mendenhall, Erzsébet Merényi:
Minimum Surface Bhattacharyya feature selection. WHISPERS 2009: 1-4 - [c16]Michael J. Mendenhall, Erzsébet Merényi:
On the evaluation of synthetic hyperspectral imagery. WHISPERS 2009: 1-4 - [c15]Bei Xie, Tamal Bose, Erzsébet Merényi:
A novel scheme for the compression and classification of hyperspectral images. WHISPERS 2009: 1-4 - [c14]Lili Zhang, Erzsébet Merényi, William M. Grundy, Eliot F. Young:
An SOM-Hybrid Supervised Model for the Prediction of Underlying Physical Parameters from Near-Infrared Planetary Spectra. WSOM 2009: 362-371 - 2008
- [j5]Michael J. Mendenhall, Erzsébet Merényi:
Relevance-Based Feature Extraction for Hyperspectral Images. IEEE Trans. Neural Networks 19(4): 658-672 (2008) - [c13]Kadim Tasdemir, Erzsébet Merényi:
Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization. Discovery Science 2008: 259-271 - [c12]Thomas Villmann, Erzsébet Merényi, Udo Seiffert:
Machine learning approches and pattern recognition for spectral data. ESANN 2008: 433-444 - 2007
- [j4]Michael Biehl
Advances in computational intelligence and learning. Neurocomputing 70(7-9): 1117-1119 (2007) - [j3]Erzsébet Merényi, Abha Jain, Thomas Villmann:
Explicit Magnification Control of Self-Organizing Maps for "Forbidden" Data. IEEE Trans. Neural Networks 18(3): 786-797 (2007) - [c11]Thomas Villmann, Frank-Michael Schleif, Erzsébet Merényi, Barbara Hammer
Fuzzy Labeled Self-Organizing Map for Classification of Spectra. IWANN 2007: 556-563 - [c10]Erzsébet Merényi, Lili Zhang, Kadim Tasdemir:
Min(d)ing the small details: discovery of critical knowledge through precision manifold learning, and application to onboard decision support. SoSE 2007: 1-8 - 2006
- [c9]Lili Zhang, Erzsébet Merényi:
Weighted differential topographic function: a refinement of topographic function. ESANN 2006: 13-18 - [c8]Kadim Tasdemir, Erzsébet Merényi:
Data topology visualization for the Self-Organizing Map. ESANN 2006: 277-282 - 2004
- [c7]Abha Jain, Erzsébet Merényi:
Forbidden Magnification? I. ESANN 2004: 51-56 - [c6]Erzsébet Merényi, Abha Jain:
Forbidden magnification? II. ESANN 2004: 57-62 - [c5]Erzsébet Merényi, William H. Farrand, Philip Tracadas:
Mapping Surface Materials on Mars from Mars Pathfinder Spectral Images with HYPEREYE. ITCC (2) 2004: 607-614 - 2003
- [j2]Thomas Villmann, Erzsébet Merényi, Barbara Hammer
Neural maps in remote sensing image analysis. Neural Networks 16(3-4): 389-403 (2003) - 2002
- [c4]Donald MacDonald, Emilio Corchado, Colin Fyfe, Erzsébet Merényi:
Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit. ICANN 2002: 649-654
1990 – 1999
- 1999
- [c3]Erzsébet Merényi:
The challenges in spectral image analysis: an introduction, and review of ANN approaches. ESANN 1999: 93-98 - [c2]Jörg Bruske, Erzsébet Merényi:
Estimating the intrinsic dimensionality of hyperspectral images. ESANN 1999: 105-110 - 1998
- [j1]Erzsébet Merényi, Scott A. Starks, Karen Villaverde:
Hyper-Spectral Satellite Images: Interval Methods May Be Helpful. Reliab. Comput. 4(4): 395-397 (1998) - [c1]Erzsébet Merényi:
Self-organizing ANNs for planetary surface composition research. ESANN 1998: 197-202
Coauthor Index
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