Case-Based Reasoning on Images and Signals
This book 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 knowl...
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| Glavni autor: | |
|---|---|
| Daljnji autori: | |
| Format: | Livre numérique |
| Jezik: | Anglais |
| Izdano: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Izdanje: | 1st ed. 2008. |
| Serija: | Studies in Computational Intelligence
73 |
| Online pristup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Bilješka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Case-Based Reasoning on Images and Signals, Texte imprimé, 9783540731788 • Case-Based Reasoning on Images and Signals, Texte imprimé, 9783540848349 • Case-Based Reasoning on Images and Signals, Texte imprimé, 9783642092213 • Case-Based Reasoning on Images and Signals, Texte imprimé, 9783540731788 |
Sadržaj:
- 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