Difference between revisions of "Event:IJCNN 2009"

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|Title=International Joint Conference on Neural Networks
 
|Title=International Joint Conference on Neural Networks
 
|Type=Conference
 
|Type=Conference
|Field=Machine learning
 
 
|Homepage=ijcnn2009.com
 
|Homepage=ijcnn2009.com
 
|City=Atlanta
 
|City=Atlanta
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|Start Date=2009/06/14
 
|Start Date=2009/06/14
 
|End Date=2009/06/19
 
|End Date=2009/06/19
 +
|Academic Field=Machine Learning
 
}}
 
}}
 
IJCNN is the premier international conference in the area of neural networks theory, analysis and applications. Topics of interest include but are not restricted to:
 
IJCNN is the premier international conference in the area of neural networks theory, analysis and applications. Topics of interest include but are not restricted to:

Revision as of 13:30, 24 August 2022

IJCNN is the premier international conference in the area of neural networks theory, analysis and applications. Topics of interest include but are not restricted to:

  • Connectionist methods in cognitive science and cognitive modeling (language, reasoning,perception, learning, consciousness,emotion, etc.)
  • Computational neuroscience
  • Neuro-technologies and neuro-engineering,brain-machine interfaces
  • Cognitive robotics, developmental robotics and neural robotics
  • Data mining and pattern recognition
  • Signal processing and time series analysis
  • Image processing and machine vision
  • Neurocontrol
  • Neuroinformatics and bioinformatics
  • Hybrid neural-symbolic, neuro-fuzzy,neuro-evolutionary systems, neuro-swarm, neural dynamic logic and other methods
  • Connectionist methods of emergent intelligence
  • Bayesian models and statistical machine learning methods
  • Support vector machines and Kernel methods
  • Learning methods: supervised, unsupervised and reinforcement
  • Adaptive dynamic programming and neurodynamic optimization
  • Neural dynamics, complex systems, and chaos
  • Hardware implementations of neural networks, neuromorphic engineering
  • Intelligent tools and methods (expert systems, embedded systems, data mining, multi-agent systems)
  • Real world applications of neural networks (games, finance, social systems, biomedical, power systems, telecommunication,defense, manufacturing)
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