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Similarity-Based Pattern Analysis and Recognition
The pattern recognition and machine learning communities have, until recently, focused mainly on feature-vector representations, typically considering objects in isolation. However, this paradigm is being increasingly challenged by similarity-based approaches, which recognize the importance of relat...
| Clasificación: | Libro Electrónico |
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| Autor Corporativo: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2013.
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| Edición: | 1st ed. 2013. |
| Colección: | Advances in Computer Vision and Pattern Recognition,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Introduction
- Part I: Foundational Issues
- Non-Euclidean Dissimilarities
- SIMBAD
- Part II: Deriving Similarities for Non-vectorial Data
- On the Combination of Information Theoretic Kernels with Generative Embeddings
- Learning Similarities from Examples under the Evidence Accumulation Clustering Paradigm
- Part III: Embedding and Beyond
- Geometricity and Embedding
- Structure Preserving Embedding of Dissimilarity Data
- A Game-Theoretic Approach to Pairwise Clustering and Matching
- Part IV: Applications
- Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma
- Analysis of Brain Magnetic Resonance (MR) Scans for the Diagnosis of Mental Illness.