(mobo import Concept___Events_With_Academic_Fields-migrated) |
(mobo import Concept___Events-migrated) |
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|City=Atlanta | |City=Atlanta | ||
|State=Georgia | |State=Georgia | ||
− | |Country= | + | |Country=Country:US |
|Submission deadline=2008/12/15 | |Submission deadline=2008/12/15 | ||
|Notification=2009/01/30 | |Notification=2009/01/30 | ||
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|End Date=2009/06/19 | |End Date=2009/06/19 | ||
|Academic Field=Machine Learning | |Academic Field=Machine Learning | ||
+ | |Event Status=as scheduled | ||
+ | |Event Mode=on site | ||
}} | }} | ||
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 14:30, 6 September 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)