Description
Springer Case-Based Reasoning On Images And Signals 2007 Edition by Petra Perner
This is the first edited book that deals with the special topic of signals and images within Case-Based Reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical industrial ecological biotechnological and many other applications. Existing statistical and knowledge-based techniques lack robustness accuracy and flexibility. New strategies are needed that can adapt to changing environmental conditions signal variation user needs and process requirements. Introducing CBR strategies into signal-interpreting systems can satisfy these requirements. Table of contents : to Case-Based Reasoning for Signals and Images.- Similarity.- Distance Function Learning for Supervised Similarity Assessment.- Induction of Similarity Measures for Case Based Reasoning Through Separable Data Transformations.- Graph Matching.- Memory Structures and Organization in Case-Based Reasoning.- Learning a Statistical Model for Performance Prediction in Case-Based Reasoning.- A CBR Agent for Monitoring the Carbon Dioxide Exchange Rate from Satellite Images.- Extracting Knowledge from Sensor Signals for Case-Based Reasoning with Longitudinal Time Series Data.- Prototypes and Case-Based Reasoning for Medical Applications.- Case-Based Reasoning for Image Segmentation by Watershed Transformation.- Similarity-Based Retrieval for Biomedical Applications.- Medical Imagery in Case-Based Reasoning.- Instance-Based Relevance Feedback in Image Retrieval Using Dissimilarity Spaces.