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EI ICFNN 2019 : 2019 International Conference on Frontiers of Neural Networks (ICFNN 2019)

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Link: http://www.icfnn.org/
 
When Jul 26, 2019 - Jul 28, 2019
Where Rome,Italy
Submission Deadline Dec 30, 2018
Notification Due Dec 30, 2018
Final Version Due Dec 30, 2018
Categories    neural networks   frontiers
 

Call For Papers

★2019 International Conference on Frontiers of Neural Networks (ICFNN 2019)  - Ei Compendex & Scopus—Call for paper 
July 26-28, 2019|Rome,Italy|Website: www.icfnn.org

★Researchers, scientists, engineers and industry professionals will join together this year at ICFNN 2019, where the latest research will be unveiled and groundbreaking research projects will be presented. The field of  Frontiers of Neural Networks is entering an era of unprecedented change and innovation. ICFNN 2019 presents one of 2019’s premiere opportunities to hear from and network with an international array of experts on the ever evolving state of the field.

★Publication and Indexing
All accepted papers will be published in the digital conference proceedings which will send to be indexed by all major citation databases such as Ei Compendex, Scopus, Google Scholar, Cambridge Scientific Abstracts (CSA), Inspec, SCImago Journal & Country Rank (SJR), EBSCO, CrossRef, Thomson Reuters (WoS), etc.
A selection of papers will be recommended to be published in journals.

★Program Preview/ Program at a glance
July 26, 2019: Registration + Icebreaker Reception
July 27, 2019: Opening Ceremony+ KN Speech+ Technical Sessions 
July 28, 2019: Technical Sessions+ Half day tour/Lab tours

★Paper Submission
1. PDF version submit via CMT: https://cmt3.research.microsoft.com/ICFNN2019
2.Submit Via email directly to: icfnn@iased.org

★CONTACT US
Ms. Yedda Q. YE
Email: icfnn@iased.org
Website: www.icfnn.org


Call for papers(http://www.icfnn.org/cfp.html):
Stability and Convergence Analysis
Neural Network Models (Feedforward/Recurrent/Self-organizing/Cellular/Hybrid Neural Networks)
Supervised/Unsupervised/Reinforcement Learning/Deep Learning
Statistical Learning Algorithms (PCA, ICA, Projection Pursuit Methods)
Kernel Methods, Large Margin Methods and SVM
Optimization Algorithms / Variational Methods
Probabilistic and Information-Theoretic Methods
Mixture Models, Graphical Models, Topic Models and Gaussian Processes
Ensemble Learning, Committee Algorithms and Boosting
Bayesian, Belief, Causal and Semantic Networks
Model Selection and Structure Learning
Feature Analysis and Clustering
Sparsity and Feature Selection
Pattern Analysis and Classification
Matrix/Tensor Analysis and Factorization
Temporal Models and Sequence Data
Structured and Relational Data
Embeddings and Manifold Learning
Active Learning
Vision and Auditory Modelling
Visual Perception and Modelling
Visual Selective Attention
Statistical and Pattern Recognition
Visual Features Analysis
Object Recognition
Motion and Tracking
Natural Scene Statistics
Image Segmentation
Image Coding and Representation
Auditory Perception and Modeling
Source Separation
Speech Recognition and Speech Synthesis
Speaker Identification
Audio and Speech Retrieval
Music Modeling and Analysis
Control, Robotics and Hardware
Neuromorphic Hardware and Implementations
Embedded Neural Networks
Reconfigurable Systems
Fuzzy Neural Networks
Robotics: Neural Robotics, Cognitive Robotics, Developmental Robotics
Multi-Agent Systems and Game Theory
Reinforcement Learning
Markov Decision Processes
Planning and Decision Making
Predictive State Representations
Policy Search
Action and Motor Control
Visuomotor Control
Computational Neuroscience and Cognitive Science
Computational Neural Models
Spiking Neurons
Visual and Auditory Cortex
Neural Encoding and Decoding
Plasticity and Adaptation
Brain Imaging (fMRI, MEG, EEG)
Learning and Memory
Inference and Reasoning
Knowledge Acquisition and Language
Perception, Emotion and Development
Action and Motor Control
Attractor and Associative Memory
Neurodynamics, Complex Systems, and Chaos
Novel Approaches and Applications
Brain-Like Systems, Adaptive Intelligent Systems
Brain-Computer Interfaces
Granular Computing
Evolutionary Neural Networks
Hybrid Intelligent Systems
Bioinformatics and Biomedical Engineering
Neuroinformatics and Neuroengineering
Systems Biology
Time Series Prediction
Information Retrieval
Data Mining and Knowledge Discovery
Natural Language Processing

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