Proceedings of ELM-2014 Volume 2 [[electronic resource] ] : Applications / / edited by Jiuwen Cao, Kezhi Mao, Erik Cambria, Zhihong Man, Kar-Ann Toh

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
• Edizione: 1st ed. 2015.
• Descrizione fisica: 1 online resource (395 p.)
• Disciplina: 006.3; 620
• Soggetto topico: Computational intelligence; Artificial intelligence; Computational Intelligence; Artificial Intelligence
• Persona (resp. second.): CaoJiuwen; MaoKezhi; CambriaErik; ManZhihong; TohKar-Ann
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: 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.
• Sommario/riassunto: 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. .
• Titolo autorizzato: Proceedings of ELM-2014 Volume 2
• ISBN: 3-319-14066-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910299705503321
• Lo trovi qui: Univ. Federico II
• Serie: Proceedings in Adaptation, Learning and Optimization, . 2363-6084 ; ; 4