Proceedings of ELM-2014 Volume 2 [electronic resource] : Applications /
Cao, Jiuwen.editor.
Mao, Kezhi.editor.
Cambria, Erik.editor.
Man, Zhihong.editor.
Toh, Kar-Ann.editor.
This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”.  The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.  .
Description based upon print version of record.
Includes bibliographical references.
Using Extreme Learning Machine for Filamentous Bulking Prediction and Forecast in Wastewater Treatment Plants -- Extreme Learning Machine for Linear Dynamical Systems Classification: Application to Human Activity Recognition -- Lens Distortion Correction Using ELM -- Pedestrian Detection in Thermal Infrared Image using Extreme Learning Machine -- Dynamic Texture Video Classification Using Extreme Learning Machine -- Uncertain XML Documents Classification Using Extreme Learning Machine -- Encrypted traffic identification based on randomness sparse feature and extreme learning machine -- Network Intrusion Detection Based on Extreme Learning Machine -- A Study on Three-dimensional Motion History Image and Extreme Learning Machine Oriented Body Movements Trajectory Recognition -- An Improved ELM Algorithm for the Measurement of Hot Metal Temperature in Blast Furnace -- Wi-Fi and Motion Sensors based Indoor Localization Combining ELM and Particle Filter -- Online Sequential Extreme Learning Machine for Watermarking -- Adaptive neural control of quadrotor helicopter with extreme learning machine -- Keyword Search on Probabilistic XML Data based on ELM -- A Novel HVS Based Gray Scale Image Watermarking Scheme Using Fast Fuzzy - ELM Hybrid Architecture -- Wearable EyeGlass based Fall Detection using Weighted ELM -- Concise Feature Extraction based ELM for Active Service Quality Prediction -- Multi-class AdaBoost ELM and Its Application in LBP Based Face Recognition -- Detecting Copy Directions among Programs Using Extreme Learning Machines -- Extreme learning machine for reservoir parameter estimation in heterogeneous reservoir -- Multifault Diagnosis for Rolling Element Bearings Based on Extreme Learning Machine -- Gradient-based No-Reference Image Blur Assessment Using Extreme Learning Machine -- RFID Enabled Indoor Positioning for Real-time Manufacturing Execution System based on OS-ELM -- An Online Sequential Extreme Learning Machine for Tidal Prediction based on Improved Gath-Geva Fuzzy Segmentation -- Recognition of Human Stair Ascent and Descent Activities based on Extreme Learning Machine -- ELM Based Dynamic Modeling for Online Prediction of Content in Molten Iron --  Distributed Learning over Massive XML Documents in ELM Feature Space -- Hyperspectral Image Nonlinear Unmixing by Ensemble ELM Regression -- Text-Image Separation and Indexing in Historic Patent Document Image Based on Extreme Learning Machine -- Anomaly Detection with ELM-based Visual Attribute and Spatio-temporal Pyramid -- Modelling and Prediction of Surface Roughness and Power Consumption using Parallel Extreme Learning Machine based Particle Swarm Optimization -- OS-ELM based Emotion Recognition for Empathetic Elderly Companion -- Access Behavior Prediction in Distributed StorageSystem using Regularized Extreme Learning Machine -- ELM Based Fast CFD Model with Sensor Adjustment -- Melasma Image Segmentation Using Extreme Learning Machine -- Detection of Drivers' Distraction Using Semi-Supervised Extreme Learning Machine -- Driver Workload Detection in On-road Driving Environment using Machine Learning.
This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”.  The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.  .
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.