Case-Based Reasoning on Images and Signals
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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.
- Introduction to Case-Based Reasoning
- Similarity
- Learning Distance Functions 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
- Applications
- A CBP agent for monitoring the ocean CO2 exchange rate
- Classification and Identification of Significant Information in Sensor Signals in Medical Applications
- Prototypes and Case-Based Reasoning for Medical Applications
- Case-based Reasoning for Image Segmentation by Watershed Transformation
- Similarity-based Retrieval and Indexing in the Biomedical Context
- Medical Imagery in Case-Based Reasoning
- Instance-Based Relevance Feedback in Image Retrieval Using Dissimilarity Spaces
- 2007, X, 436 Seiten, Maße: 16,4 x 24,3 cm, Kartoniert (TB), Englisch
- Herausgegeben: Petra Perner
- Verlag: Springer Berlin
- ISBN-10: 3540731784
- ISBN-13: 9783540731788
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