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FLAIRS-36 ST NN DM 2023 : FLAIRS-36 Special Track on Neural Networks and Data Mining

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Link: https://sites.google.com/view/flairs-36-nn-dm-track/home
 
When May 14, 2023 - May 17, 2023
Where Clearwater Beach, FL
Abstract Registration Due Feb 6, 2023
Submission Deadline Feb 13, 2023
Notification Due Mar 13, 2023
Final Version Due Apr 10, 2023
Categories    neural networks   data mining   deep learning
 

Call For Papers

Papers are being solicited for a special track on Neural Networks and Data Mining at the 36th International FLAIRS Conference (https://www.flairs-36.info/home). This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy Logic applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction; and knowledge engineering or warehousing.

Questions regarding the track should be addressed to: David Bisant at bisant@umbc.edu, Steven Gutstein at s.m.gutstein@gmail.com, or Bill Eberle at weberle@tntech.edu.

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