Similarity-Based Pattern Analysis and Recognition

1. Introduction: The SIMBAD Project
Marcello Pelillo

Part I. Foundational Issues

2. Non-Euclidean Dissimilarities: Causes, Embedding and Informativeness
Robert P. W. Duin, Elżbieta Pękalska, Marco Loog

3. SIMBAD: Emergence of Pattern Similarity
Joachim M. Buhmann

Part II. Deriving Similarities for Non-vectorial Data

4. On the Combination of Information-Theoretic Kernels with Generative Embeddings
Pedro M. Q. Aguiar, Manuele Bicego, Umberto Castellani, Mário A. T. Figueiredo, André T. Martins, Vittorio Murino, Alessandro Perina, Aydın Ulaş

5. Learning Similarities from Examples Under the Evidence Accumulation Clustering Paradigm
Ana L. N. Fred, André Lourenço, Helena Aidos, Samuel Rota Bulò, Nicola Rebagliati, Mário A. T. Figueiredo, Marcello Pelillo

Part III. Embedding and Beyond

6. Geometricity and Embedding
Peng Ren, Furqan Aziz, Lin Han, Eliza Xu, Richard C. Wilson, Edwin R. Hancock

7. Structure Preserving Embedding of Dissimilarity Data
Volker Roth, Thomas J. Fuchs, Julia E. Vogt, Sandhya Prabhakaran, Joachim M. Buhmann

8. A Game-Theoretic Approach to Pairwise Clustering and Matching
Marcello Pelillo, Samuel Rota Bulò, Andrea Torsello, Andrea Albarelli, Emanuele Rodolà

Part IV. Applications

9. Automated Analysis of Tissue Micro-Array Images on the Example of Renal Cell Carcinoma
Peter J. Schüffler, Thomas J. Fuchs, Cheng Soon Ong, Volker Roth, Joachim M. Buhmann

10. Analysis of Brain Magnetic Resonance (MR) Scans for the Diagnosis of Mental Illness
Aydın Ulaş, Umberto Castellani, Manuele Bicego, Vittorio Murino, Marcella Bellani, Michele Tansella, Paolo Brambilla

Nyckelord: Computer Science, Pattern Recognition