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ESANN 2024 : 32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

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Conference Series : The European Symposium on Artificial Neural Networks
 
Link: https://www.esann.org/
 
When Oct 9, 2024 - Oct 11, 2024
Where Bruges, Belgium
Submission Deadline May 2, 2024
Notification Due Jun 16, 2024
Categories    neural networks   computational intelligence   machine learning
 

Call For Papers

The 32th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning will be organized in hybrid mode, from Wednesday 9 to Friday 11 October 2024. Both in-person and online participation will be possible.

Since its first happening in 1993, the European Symposium on Artificial Neural Networks has become the reference for researchers on fundamentals and theoretical aspects of artificial neural networks, computational intelligence, machine learning and related topics. Each year, around 100-140 specialists attend ESANN, in order to present their latest results and comprehensive surveys, and to discuss the future developments in this field.

The ESANN 2024 conference will follow this tradition, while adapting its scope to the recent developments in the field. The ESANN conferences cover artificial neural networks, machine learning, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered.

Papers will be presented orally (single track) and in poster sessions; all posters will be complemented by a short oral presentation during a plenary session. The selection of papers will differentiate between oral and posters presentations according to the topics, and not to the level of quality.


The following is a non-exhaustive list of machine learning, computational intelligence and artificial neural networks topics covered during the ESANN conferences:

Track 1: THEORY and METHODS Track 2: INFORMATION PROCESSING and APPLICATIONS
Neural networks Data mining
Deep learning Signal processing and modeling
Kernel machines Machine learning for signal processing
Transfer learning Approximation and identification
Graphical models, EM and Bayesian learning Classification and clustering
Vector quantization and self-organizing maps Image processing
Recurrent networks and dynamical systems Time series forecasting
Singe- and zero-shot learning Multimodal interfaces and multichannel processing
Ensemble learning Vision and sensory systems
Nonlinear projection and data visualization Identification of non-linear dynamical systems
Feature selection Machine learning for healthcare
Evolutionary computation for machine learning Bioinformatics
Bio-inspired systems Brain-computer interfaces
Graphs and networks
Statistical and mathematical aspects of learning


Special sessions

Special sessions will be organized by renowned scientists in their respective fields. Papers submitted to these sessions are reviewed according to the same criteria as the submissions to the regular sessions. Authors who submit a paper to one of these sessions are invited to mention it on the author submission form. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures.

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