Case-based reasoning on images and signals
著者
書誌事項
Case-based reasoning on images and signals
（Studies in computational intelligence, v. 73）
Springer, c2008
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注記
Includes bibliographical references
内容説明・目次
内容説明
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.
目次
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.
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