Kar ann toh (107 resultados)

hardcover. Condición: Very Good. Fast Shipping - Safe and Secure 7 days a week.

235 mm x 155 mm. 300 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Evolutionary Learning and Optimization ; 16. Sprache: Englisch.…

Condición: Very Good. 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. Due to the weight of the book, additional postage will be required for standard international orders. ~SP05~ [2.5P] 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. 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.…

Hardcover. Condición: New. US SELLER SHIPS FAST FROM USA.

Hardcover. Condición: New. US SELLER SHIPS FROM USA.

Condición: new.

Condición: New.

Hardcover. Condición: new. Hardcover. This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Both the primal and dual solution forms are discussed for over-and under-determined systems. Such coverage provides an important perspective for handling systems with overwhelming samples or systems with overwhelming parameters. For goal driven classification, the solutions to minimum classification-error, maximum receiver operating characteristics, bridge regression, and ensemble learning represent recent advancements in the literature. In this book, the exercises offer instructors and students practical experience with real-world applications. This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Condición: new.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. In English.

Condición: New. In English.

Paperback. Condición: New.

Condición: New.

Condición: New.

Condición: New. pp. 225.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Both the primal and dual solution forms are discussed for over-and under-determined systems. Such coverage provides an important perspective for handling systems with overwhelming samples or systems with overwhelming parameters. For goal driven classification, the solutions to minimum classification-error, maximum receiver operating characteristics, bridge regression, and ensemble learning represent recent advancements in the literature.In this book, the exercises offer instructors and students practical experience with real-world applications. …

Taschenbuch. Condición: Neu. Analytic Learning Methods for Pattern Recognition | Kar-Ann Toh (u. a.) | Taschenbuch | xx | Englisch | 2026 | Springer | EAN 9789819621538 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condición: As New. Unread book in perfect condition.

Condición: New. pp. vi + 225.

Hardback. Condición: New. This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Both the primal and dual solution forms are discussed for over-and under-determined systems. Such coverage provides an important perspective for handling systems with overwhelming samples or systems with overwhelming parameters. For goal driven classification, the solutions to minimum classification-error, maximum receiver operating characteristics, bridge regression, and ensemble learning represent recent advancements in the literature. In this book, the exercises offer instructors and students practical experience with real-world applications.…

Taschenbuch. Condición: Neu. Extreme Learning Machines 2013: Algorithms and Applications | Fuchen Sun (u. a.) | Taschenbuch | Adaptation, Learning, and Optimization | vi | Englisch | 2016 | Springer | EAN 9783319350035 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Hardcover. Condición: Brand New. 300 pages. 9.25x6.10x0.80 inches. In Stock.

Hardcover. Condición: Brand New. 350 pages. 9.26x6.11x9.21 inches. In Stock.

Condición: New.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discussions of 'learning without iterative tuning'.This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM.…

Paperback. Condición: Brand New. reprint edition. 232 pages. 9.25x6.10x0.55 inches. In Stock.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Both the primal and dual solution forms are discussed for over-and under-determined systems. Such coverage provides an important perspective for handling systems with overwhelming samples or systems with overwhelming parameters. For goal driven classification, the solutions to minimum classification-error, maximum receiver operating characteristics, bridge regression, and ensemble learning represent recent advancements in the literature.In this book, the exercises offer instructors and students practical experience with real-world applications.…

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discussions of 'learning without iterative tuning'.This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM.…