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Satellite Image Analysis Clustering and Classification

readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques;

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Image Analysis, Classification, and Change Detection in Remote Sensing

sensing. Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL combines theory, algorithms, and;

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Image Analysis and Recognition

. The papers are organized in topical sections on clustering and classification; image processing; image analysis; motion analysis and tracking;

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Image Analysis and Recognition

. The papers are organized in topical sections on clustering and classification; image processing; image analysis; motion analysis and tracking;

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Object-Based Image Analysis and Treaty Verification

, feature extraction, change detection, classification and interpretation are developed, applied and evaluated. The analysis chain is demonstrated;

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Data Clustering

on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50;

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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

organized in topical sections on image coding, processing and analysis; segmentation, analysis of shape and texture; analysis of signal, speech and;

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KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis

Knn Classifier and K-Means Clustering Fo;

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Advances in Face Detection and Facial Image Analysis

analysis, facial dynamics analysis, face classification, identification, and clustering, and gaze direction and head pose estimation, as well as;

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Advances in Face Detection and Facial Image Analysis

dynamics analysis, face classification, identification, and clustering, and gaze direction and head pose estimation, as well as applications;

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Computational Intelligence in Pattern Recognition

This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft;

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Advanced Analysis and Learning on Temporal Data

and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on;

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Advances in Knowledge Discovery and Data Mining

and selected from 307 submissions. They are organized in topical sections named: classification; machine learning; applications; novel;

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Advances in Knowledge Discovery and Data Mining

and selected from 307 submissions. They are organized in topical sections named: classification; machine learning; applications; novel;

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Model-Based Clustering and Classification for Data Science

Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many;

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Topics in Medical Image Processing and Computational Vision

Disease Classification, Video Understanding and Management, Image Processing, Image Segmentation, Bio-structure Modelling and Simulation, Medical;

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Tensor Computation for Data Analysis

of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational;

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Intelligent Data Engineering and Automated Learning - IDEAL 2016

; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological;

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Pattern Recognition and Image Processing

imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition;

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Computational Intelligence Paradigms in Advanced Pattern Classification

This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting;

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Remotely Sensed Data Characterization, Classification, and Accuracies

A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the;

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Biomedical Image Understanding

Understanding focuses on image understanding and semantic interpretation, with clear introductions to related concepts, in-depth theoretical analysis;

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Data Clustering and Image Segmentation Through Genetic Algorithms

principles. Featuring research on topics such as cluster analysis, metaheuristic optimization, and image processing, this book is ideally designed;

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Recent Trends in Signal and Image Processing

recognition, reconstruction and fractal analysis. It addresses various types of signals, such as image, video, speech, non-speech audio, handwritten;

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Evolutionary Data Clustering

clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and;

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply;

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Digital Image Processing

, biomedical application and other diverse fields of material science, robotics etc. This book deals primarily with analysis of digital images acquired;

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