Electronic proceedings author index

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
J. Seal
  • ESANN 1995 - A distribution-based model of the dynamics of neural networks in the cerebral cortex [Details]
M. Sebag
  • ESANN 1999 - From first order logic to Nd: a data driven reformulation [Details]
P. Sebire
  • ESANN 1993 - MLP modular networks for multi-class recognition [Details]
Konstantinos Sechidis
  • ESANN 2017 - Algorithmic challenges in big data analytics [Details]
  • ESANN 2019 - Multi-target feature selection through output space clustering [Details]
Ismaila Seck
  • ESANN 2019 - L1-norm double backpropagation adversarial defense [Details]
Reza Sedghi
  • ESANN 2025 - Early Prediction of Dynamic Sparsity in Large Language Models [Details]
Michael Sedlmair
  • ESANN 2016 - Human-centered machine learning through interactive visualization: review and open challenges [Details]
  • ESANN 2018 - VisCoDeR: A tool for visually comparing dimensionality reduction algorithms [Details]
Matthias Seeger
  • ESANN 2008 - Learning Inverse Dynamics: a Comparison [Details]
Oliver Sefrin
  • ESANN 2025 - Encoding hyperspectral data with low-bond dimension quantum tensor networks [Details]
Itai Segall
  • ESANN 2017 - Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure [Details]
Enrique Carlos Segura
  • No papers found
S. Sehad
  • ESANN 1994 - Reinforcement learning and neural reinforcement learning [Details]
F. Seifart
  • ESANN 2003 - A neural model for heading detection from optic flow [Details]
Michael Seifert
  • ESANN 2012 - Posterior regularization and attribute assessment of under-determined linear mappings [Details]
Udo Seiffert
  • ESANN 2022 - Federated learning vector quantization for dealing with drift between nodes [Details]
  • ESANN 2022 - From hyperspectral to multispectral sensing – from simulation to reality: A comprehensive approach for calibration model transfer [Details]
Udo Seiffert
  • ESANN 2021 - Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data [Details]
Udo Seiffert
  • No papers found
Udo Seiffert
  • ESANN 2004 - Theory and applications of neural maps [Details]
  • ESANN 2005 - Generalized Relevance LVQ with Correlation Measures for Biological Data [Details]
  • ESANN 2006 - Fuzzy image segmentation with Fuzzy Labelled Neural Gas [Details]
  • ESANN 2006 - Neural networks and machine learning in bioinformatics - theory and applications [Details]
  • ESANN 2006 - Sanger-driven MDSLocalize - a comparative study for genomic data [Details]
  • ESANN 2007 - Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS [Details]
  • ESANN 2008 - Machine learning approches and pattern recognition for spectral data [Details]
  • ESANN 2010 - Validation of unsupervised clustering methods for leaf phenotype screening [Details]
  • ESANN 2011 - Recent trends in computational intelligence in life sciences [Details]
  • ESANN 2012 - Classifying Scotch Whisky from near-infrared Raman spectra with a Radial Basis Function Network with Relevance Learning [Details]
  • ESANN 2012 - Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting [Details]
  • ESANN 2013 - Processing Hyperspectral Data in Machine Learning [Details]
  • ESANN 2019 - Transfer Learning for transferring machine-learning based models among hyperspectral sensors [Details]
Udo Seiffert
  • ESANN 2025 - Machine Learning on Smartphone-Captured Diffraction Data [Details]
U. Seiffert
  • ESANN 2001 - Multiple Layer Perceptron training using genetic algorithms [Details]
  • ESANN 2002 - Artificial Neural Networks on Massively Parallel Computer Hardware [Details]
  • ESANN 2003 - Digital Image Processing with Neural Networks [Details]
Borja Seijo-Pardo
  • ESANN 2016 - Using a feature selection ensemble on DNA microarray datasets [Details]
  • ESANN 2018 - Analysis of imputation bias for feature selection with missing data [Details]
T. Seiler
  • ESANN 1998 - Perception and action selection by anticipation of sensorimotor consequences [Details]
S. Seki
  • ESANN 2003 - Cellular topographic self-organization under correlational learning [Details]
Abderrahim Sellami
  • ESANN 2013 - Machine Learning Techniques for Short-Term Electric Power Demand Prediction [Details]
  • ESANN 2013 - Temperature Forecast in Buildings Using Machine Learning Techniques [Details]
Mokhtar Sellami
  • ESANN 2005 - Artificial neural network fusion: Application to Arabic words recognition [Details]
Bernhard Sendhoff
  • ESANN 2005 - Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study [Details]
  • ESANN 2005 - Synergies between Evolutionary and Neural Computation [Details]
Stephane Senecal
  • ESANN 2014 - Extreme learning machines for Internet traffic classification [Details]
Mathieu Senelle
  • ESANN 2014 - The Sum-over-Forests clustering [Details]
Debarka Sengupta
  • ESANN 2021 - Enhash: A Fast Streaming Algorithm For Concept Drift Detection [Details]
Jose A. Seoane
  • ESANN 2014 - A Random Forest proximity matrix as a new measure for gene annotation [Details]