عنوان

Neurocomputation in Remote Sensing Data Analysis Proceedings of Concerted Action COMPARES (Connectionist Methods for Pre-Processing and Analysis of Remote Sensing Data)

(Number (ISBN

3642638287

(Number (ISBN

9783642638282

Number

b536125

Title Proper

Neurocomputation in Remote Sensing Data Analysis Proceedings of Concerted Action COMPARES (Connectionist Methods for Pre-Processing and Analysis of Remote Sensing Data)

General Material Designation

[Book]

First Statement of Responsibility

Ioannis Kanellopoulos

Name of Publisher, Distributor, etc.

Berlin Springer Berlin

Date of Publication, Distribution, etc.

2013

Specific Material Designation and Extent of Item

IX, 284 Seiten in 1 Teil IX, 284 Seiten, 39 schw.-w. Tabellen 235 x 155 mm

Text of Note

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

Class number

Book number

Ioannis Kanellopoulos

Fabio Roli

Graeme G Wilkinson

Ioannis Kanellopoulos

James Austin

Electronic name

[Book]

Y