ICANN 2020 : International Conference on Artificial Neural Networks

in Conferences   Posted on December 10, 2019 

Conference Information

Submission Deadline Sunday 15 Mar 2020 Proceedings indexed by :
Conference Dates Sep 15, 2020 - Sep 18, 2020
Conference Address Bratislava, Slovakia
Conference & Submission Link https://e-nns.org/icann2020/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Impact Score 3.46
#Contributing Top Scientists 39
#Papers published by Top Scientists 61
Google Scholar H5-index 19
Number of Editions: 29 (Since 1991)
Guide2Research Overall Ranking: 190
Category Rankings
Machine Learning & Artificial Intelligence 56
Proceedings https://link.springer.com/conference/icann
DBLP Page https://dblp.uni-trier.de/db/conf/icann

Conference Call for Papers

Conference proceedings are published by Springer in Lecture Notes in Computer Science.

The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). The ideal of ICANN is to bring together researchers from two worlds: information sciences and neurosciences. The scope is wide, ranging from machine learning algorithms to models of real nervous systems. The aim is to facilitate discussions and interactions in the effort towards developing more intelligent computational systems and increasing our understanding of neural and cognitive processes in the brain.

Conference topics
ICANN 2020 will feature two main tracks: Brain inspired computing and Machine learning research, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the Conference

Neural Network Theory
Neural Network Models
Graphical Models
Bayesian Networks
Kernel Methods
Generative Models
Information Theoretic Learning
Reinforcement Learning
Relational Learning
Dynamical Models
Recurrent Networks.
Cognitive models
Computational Neuroscience
Reinforcement Learning
Neural Control and Planning
Hybrid Neural-Symbolic Architectures
Neural Dynamics
Intelligent Robotics
Language Processing
Image Processing
Sensor Fusion
Pattern Recognition
Data Mining
Neural Agents
Brain-Computer Interaction
Neural Hardware
Evolutionary Neural Networks

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