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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 relational and similarity information. This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: Explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms Reviews similarity measures for non-vectorial data, considering both a “kernel tailoring” approach and a strategy for learning similarities directly from training data Describes various methods for “structure-preserving” embeddings of structured data Formulates classical pattern recognition problems from a purely game-theoretic perspective Examines two large-scale biomedical imaging applications that provide assistance in the diagnosis of physical and mental illnesses from tissue microarray images and MRI images This pioneering work is essential reading for graduate students and researchers seeking an introduction to this important and diverse subject. Marcello Pelillo is a Full Professor of Computer Science at the University of Venice, Italy. He is a Fellow of the IEEE and of the IAPR.

Mathematical statistics --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- MRI (magnetic resonance imaging) --- patroonherkenning --- factoranalyse --- machine learning --- microarrays --- computers --- computerkunde --- optica

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This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation.

Computer science. --- Arithmetic and logic units, Computer. --- Numerical analysis. --- Computer science --- Artificial intelligence. --- Image processing. --- Pattern recognition. --- Computer Science. --- Pattern Recognition. --- Arithmetic and Logic Structures. --- Image Processing and Computer Vision. --- Numeric Computing. --- Math Applications in Computer Science. --- Artificial Intelligence (incl. Robotics). --- Mathematics. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer mathematics --- Discrete mathematics --- Mathematical analysis --- Arithmetic and logic units, Computer --- Computer arithmetic --- Electronic digital computers --- Informatics --- Science --- Mathematics --- Circuits --- Optical pattern recognition. --- Computer vision. --- Electronic data processing. --- Artificial Intelligence. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Pattern perception --- Perceptrons --- Visual discrimination --- Automation --- Computer vision --- Optical data processing. --- Computer science—Mathematics. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Optical equipment

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This book constitutes the proceedings of the Second International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2013, which was held in York, UK, in July 2013. The 18 papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of problems and perspectives, from supervised to unsupervised learning, from generative to discriminative models, from theoretical issues to real-world practical applications, and offer a timely picture of the state of the art in the field.

Complex analysis --- Mathematical statistics --- Computer science --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- patroonherkenning --- beeldverwerking --- factoranalyse --- complexe analyse (wiskunde) --- bedrijfssoftware --- computers --- informatiesystemen --- database management --- KI (kunstmatige intelligentie) --- computerkunde --- robots --- optica --- AI (artificiële intelligentie)

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This book constitutes the refereed proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'97, held in Venice, Italy, in May 1997. The book presents 29 revised full papers selected from a total of 62 submissions. Also included are four full invited papers and a keynote paper by leading researchers. The volume is organized in sections on contours and deformable models, Markov random fields, deterministic methods, object recognition, evolutionary search, structural models, and applications. The volume is the first comprehensive documentation of the application of energy minimization techniques in the areas of compiler vision and pattern recognition.

Computer vision --- Pattern recognition systems --- Neural networks (Computer science) --- Evolutionary computation --- Simulated annealing (Mathematics) --- Congresses. --- Applied Physics --- Engineering & Applied Sciences --- Congresses --- Algorithm, Annealing --- Algorithm, Probabilistic exchange --- Annealing, Monte Carlo --- Annealing, Simulated --- Annealing algorithm --- Cooling, Statistical --- Exchange algorithm, Probabilistic --- Hill climbing, Probabilistic --- Monte Carlo annealing --- Probabilistic exchange algorithm --- Probabilistic hill climbing --- Relaxation, Stochastic --- Statistical cooling --- Stochastic relaxation --- Computer science. --- Computers. --- Algorithms. --- Artificial intelligence. --- Computer graphics. --- Image processing. --- Pattern recognition. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Pattern Recognition. --- Image Processing and Computer Vision. --- Computer Graphics. --- Algorithm Analysis and Problem Complexity. --- Computation by Abstract Devices. --- Optical pattern recognition. --- Computer vision. --- Computer software. --- Artificial Intelligence. --- Software, Computer --- Computer systems --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Informatics --- Science --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Digital techniques --- Optical data processing. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Cybernetics --- Calculators --- Cyberspace --- Algorism --- Algebra --- Arithmetic --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Foundations --- Optical equipment --- Computer vision - Congresses. --- Pattern recognition systems - Congresses. --- Neural networks (Computer science) - Congresses. --- Evolutionary computation - Congresses. --- Simulated annealing (Mathematics) - Congresses. --- Pattern perception.

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This book constitutes the proceedings of the Third International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2015, which was held in Copenahgen, Denmark, in October 2015. The 15 full and 8 short papers presented were carefully reviewed and selected from 30 submissions.The workshop focus on problems, techniques, applications, and perspectives: from supervised to unsupervised learning, from generative to discriminative models, and from theoretical issues to empirical validations.

Computer Science --- Electrical Engineering --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Computer science. --- Algorithms. --- Database management. --- Artificial intelligence. --- Image processing. --- Pattern recognition. --- Computer Science. --- Pattern Recognition. --- Image Processing and Computer Vision. --- Artificial Intelligence (incl. Robotics). --- Database Management. --- Algorithm Analysis and Problem Complexity. --- Information Systems Applications (incl. Internet). --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Algorism --- Algebra --- Arithmetic --- Informatics --- Science --- Foundations --- Optical pattern recognition. --- Computer vision. --- Computer software. --- Artificial Intelligence. --- Software, Computer --- Computer systems --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Pattern perception --- Perceptrons --- Visual discrimination --- Computer vision --- Optical data processing. --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment