Proceedings of ELM-2014 Volume 2: Applications (Proceedings in Adaptation, Learning and Optimization)

2015 Springer International (Cham, Switzerland), 6 1/2 x 9 1/2 inches tall pictorial hardcover, no dust jacket (as issued), illustrated with black-and-white photographs, charts and graphs, viii, 400 pp. Slight bumping to edges of covers. Otherwise, a very good to near fine copy - clean, bright and unmarked. 

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.

Contents:

• 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