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" Neurocomputation in Remote Sensing Data Analysis Proceedings of Concerted Action COMPARES (Connectionist Methods for Pre-Processing and Analysis of Remote Sensing Data) "
Ioannis Kanellopoulos
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BL
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| Record Number
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716442
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b536125
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| Main Entry
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Ioannis Kanellopoulos
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| Title & Author
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Neurocomputation in Remote Sensing Data Analysis Proceedings of Concerted Action COMPARES (Connectionist Methods for Pre-Processing and Analysis of Remote Sensing Data)\ Ioannis Kanellopoulos
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| Publication Statement
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Berlin Springer Berlin, 2013
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| Page. NO
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IX, 284 Seiten in 1 Teil IX, 284 Seiten, 39 schw.-w. Tabellen 235 x 155 mm
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| ISBN
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3642638287
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: 9783642638282
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| Contents
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Foreward - Introduction - Open Questions in Neurocomputing for Earth Observation - A Comparison of the Characterisation of Agricultural Land Using Singular Value Decomposition and Neural Networks - Land Cover Mapping from Remotely Sensed Data with a Neural Network: Accomodation Fuzziness - Geological Mapping Using Multi-Sensor Data: A Comparison of Methods - Application of Neural Networks and Order Statistics Filters to Speckle Noise Reduction in Remote Sensing Imaging - Neural Nets and Multichannel Image Processing Applications - Neural Networks for Classification of Ice Type Concentration from ERS-1 SAR Images. Classical Methods versus Neural Networks - A Neural Network Approach to Spectral Mixture Analysis - Comparison Between Systems of Image Interpretation - Feature Extraction for Neural Network Classifiers - Spectral Pattern Recognition by a Two-Layer Perceptron: Effects of Training Set Size - Comparison and Combination of Statistical and Neural Network Algorithms for Remote-Sensing Image Classification - Integrating the Alisa Classifier with Knowledge-Based Methods for Cadastral-Map Interpretation - A Hybrid Method for Preprocessing and Classification of SPOT Images - Testing some Connectionist Approaches for Thematic Mapping of Rural Areas - Using Artificial Recurrent Neural Nets to Identify Spectral and Spatial Patterns for Satellite Imagery Classification of Urban Areas - Dynamic Segmentation of Satellite Images Using Pulsed Coupled Neural Networks - Non-Linear Diffusion as a Neuron-Like Paradigm for Low-Level Vision - Application of the Constructive Mikado-Algorithm on Remotely Sensed Data - A Simple Neural Network Contextual Classifier - Optimising Neural Networks for Land Use Classification - High Speed Image Segmentation Using a Binary Neural Network - Efficient Processing and Analysis of Images Using Neural Networks - Selection of the Number of Clusters in Remote Sensing Images by Means of Neural Networks - A Comparative Study of Topological Feature Maps Versus Conventional Clustering for (Multi-Spectral) Scene. Identification in METEOSAT Imagery - Self Organised Maps: the Combined Utilisation of Feature and Novelty Detectors - Generalisation of Neural Network Based Segmentation. Results for Classification Purposes - Remote Sensing Applications which may be Addressed by Neural Networks Using Parallel Processing Technology - General Discussion
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| LC Classification
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G70.39I536 2013
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| Added Entry
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Fabio Roli
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Graeme G Wilkinson
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Ioannis Kanellopoulos
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James Austin
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