Trends in extreme learning machines: A review
Top Cited Papers
- 1 January 2015
- journal article
- review article
- Published by Elsevier BV in Neural Networks
- Vol. 61, 32-48
- https://doi.org/10.1016/j.neunet.2014.10.001
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61273233, 41427806)
- Research Fund for the Doctoral Program of Higher Education (20120002110035, 20130002130010)
- National Key Technology R&D Program (2012BAF01B03)
This publication has 100 references indexed in Scilit:
- Automatic recognition of epileptic EEG patterns via Extreme Learning Machine and multiresolution feature extractionExpert Systems with Applications, 2013
- Multifocal electroretinogram diagnosis of glaucoma applying neural networks and structural pattern analysisExpert Systems with Applications, 2012
- Application of extreme learning machine for series compensated transmission line protectionEngineering Applications of Artificial Intelligence, 2011
- Hyperspectral species mapping for automatic weed control in tomato under thermal environmental stressComputers and Electronics in Agriculture, 2011
- Optimization method based extreme learning machine for classificationNeurocomputing, 2010
- A fast recognition framework based on extreme learning machine using hybrid object informationNeurocomputing, 2010
- NASS: An empirical approach to spike sorting with overlap resolution based on a hybrid noise-assisted methodologyJournal of Neuroscience Methods, 2010
- Enhanced random search based incremental extreme learning machineNeurocomputing, 2008
- Incremental extreme learning machine with fully complex hidden nodesNeurocomputing, 2008
- Support-vector networksMachine Learning, 1995