Data Fusion Methodology and Applications(Data Handling in Science and Technology Vol.31) P 400 p. 19
目次
1. Introduction: ways and means to deal with data from multiple sources 2. Framework for low-level data fusion 3. General framing of low-high-mid level Data Fusion with examples in life science 4. Numerical optimization based algorithms for data fusion 5. Recent advances in High-Level Fusion Methods to classify multiple analytical Chemical Data 6. SO-(N)-PLS: Sequentially Orthogonalized-(N)-PLS in Data Fusion context 7. ComDim methods for the analysis of multi block data in a data fusion perspective 8. Data fusion via multiset analysis 9. Dealing with data heterogeneity in a data fusion perspecitve: models, methodologies, and algorithms 10. Data Fusion strategies in food analysis 11. Data fusion for image analysis 12. Data fusion using window based models: Application to outlier detection, classification, and forensic image analysis
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