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
A. Vermeulen
  • ESANN 1995 - Some new results on the coding of pheromone intensity in an olfactory sensory neuron [Details]
Pierre Vernimmen
  • ESANN 2024 - Convergence analysis of an inexact gradient method on smooth convex functions [Details]
H. Verrelst
  • ESANN 1999 - A hybrid system for fraud detection in mobile communications [Details]
Tom Verresen
  • ESANN 2025 - Exploring Model Architectures for Real-Time Lung Sound Event Detection [Details]
A. Verri
  • ESANN 1999 - Support vector machines vs multi-layer perceptrons in particle identification [Details]
Alessandro Verri
  • ESANN 2005 - Support vector algorithms as regularization networks [Details]
  • ESANN 2008 - A method for robust variable selection with significance assessment [Details]
  • ESANN 2010 - A randomized algorithm for spectral clustering [Details]
  • ESANN 2012 - Adaptive Optimization for Cross Validation [Details]
  • ESANN 2012 - Discriminant functional gene groups identification with machine learning and prior knowledge [Details]
  • ESANN 2013 - A dictionary learning based method for aCGH segmentation [Details]
Mario Versaci
  • ESANN 2004 - Disruption Anticipation in Tokamak Reactors: A Two-Factors Fuzzy Time Series Approach [Details]
Robin Verschuren
  • ESANN 2024 - Graph-cut-assisted CNN training for pulmonary embolism segmentation [Details]
C. Versino
  • ESANN 1993 - An intuitive characterization for the reference vectors of a Kohonen map [Details]
Timothy Verstraeten
  • ESANN 2019 - Deep hybrid approach for 3D plane segmentation [Details]
David Verstraeten
  • ESANN 2005 - Isolated word recognition using a Liquid State Machine [Details]
  • ESANN 2007 - Adapting reservoir states to get Gaussian distributions [Details]
  • ESANN 2007 - An overview of reservoir computing: theory, applications and implementations [Details]
  • ESANN 2010 - Extending reservoir computing with random static projections: a hybrid between extreme learning and RC [Details]
Lyan Verwimp
  • ESANN 2020 - On the long-term learning ability of LSTM LMs [Details]
Jean-Marc Vesin
  • ESANN 2006 - Spatial filters for the classification of event-related potentials [Details]
Benedikt Vettelschoss
  • ESANN 2020 - Self-organized dynamic attractors in recurrent neural networks [Details]
Sebastian Vetter
  • ESANN 2021 - AGLVQ - Making Generalized Vector Quantization Algorithms Aware of Context [Details]
Giuseppe Vettigli
  • ESANN 2021 - Weightless Neural Networks for text classification using tf-idf [Details]
Gizelle Vianna
  • ESANN 2017 - A decision support system based on cellular automata to help the control of late blight in tomato cultures [Details]
Dolores Vicente
  • ESANN 2005 - Handling outliers and missing data in brain tumour clinical assessment using t-GTM [Details]
A. Vicino
  • ESANN 2000 - Financial predictions based on bootstrap-neural networks [Details]
F.J. Vico
  • ESANN 1993 - Modelling biological learning from its generalization capacity [Details]
Quentin Victor
  • ESANN 2025 - Investigating four deep learning approaches as candidates for unified models in time series forecasting and event prediction: application in anesthesia training [Details]
Eva Vidal
  • ESANN 2004 - BIOSEG: a bioinspired vlsi analog system for image segmentation [Details]
Franck Vidal
  • ESANN 2005 - Neuromimetic model of interval timing [Details]
David Vieira
  • ESANN 2016 - Sparse Least Squares Support Vector Machines via Multiresponse Sparse Regression [Details]
Daniel Vieira
  • ESANN 2018 - Vector Field Based Neural Networks [Details]
E. Viennet
  • ESANN 1999 - Face identification using support vector machines [Details]
Markus Vieth
  • ESANN 2024 - Similarity-Based Zero-Shot Domain Adaptation for Wearables [Details]
F. Vietze
  • ESANN 2000 - A neural network approach to adaptive pattern analysis - the deformable feature map [Details]
Thierry Vieville
  • ESANN 2012 - Using event-based metric for event-based neural network weight adjustment [Details]
Lovekesh Vig
  • ESANN 2015 - Long Short Term Memory Networks for Anomaly Detection in Time Series [Details]
  • ESANN 2017 - TimeNet: Pre-trained deep recurrent neural network for time series classification [Details]
  • ESANN 2018 - Evolutionary RL for Container Loading [Details]
  • ESANN 2019 - Fusing Features based on Signal Properties and TimeNet for Time Series Classification [Details]