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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Pelillo, Marcello (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Springer London : Imprint: Springer, 2013.
Σειρά:Advances in Computer Vision and Pattern Recognition,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.