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Machines capable of automatic pattern recognition have many fascinating uses in science and engineering as well as in our daily lives. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. Tremendous progress has been made in refining such algorithms; yet, automatic learning in many simple tasks in daily life still appears to be far from reach. This book takes a close view of data complexity and its role in shaping the theories and techniques in different disciplines and asks: • What is missing from current classification techniques? • When the automatic classifiers are not perfect, is it a deficiency of the algorithms by design, or is it a difficulty intrinsic to the classification task? • How do we know whether we have exploited to the fullest extent the knowledge embedded in the training data? Data Complexity in Pattern Recognition is unique in its comprehensive coverage and multidisciplinary approach from various methodological and practical perspectives. Researchers and practitioners alike will find this book an insightful reference to learn about the current status of available techniques as well as application areas.

Pattern perception. --- Classification. --- Computational complexity. --- Complexity, Computational --- Electronic data processing --- Machine theory --- Knowledge, Classification of --- Information organization --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Optical pattern recognition. --- Artificial intelligence. --- Computer software. --- Pattern Recognition. --- Artificial Intelligence. --- Algorithm Analysis and Problem Complexity. --- Software, Computer --- Computer systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Pattern recognition. --- Algorithms. --- Algorism --- Algebra --- Arithmetic --- Foundations

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Complex analysis --- Mathematical statistics --- Artificial intelligence. Robotics. Simulation. Graphics --- patroonherkenning --- factoranalyse --- complexe analyse (wiskunde) --- KI (kunstmatige intelligentie) --- robots --- AI (artificiële intelligentie)

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This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018. The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods. .

Computer science. --- Data structures (Computer science). --- Algorithms. --- Computer science --- Artificial intelligence. --- Image processing. --- Pattern recognition. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Pattern Recognition. --- Image Processing and Computer Vision. --- Algorithm Analysis and Problem Complexity. --- Discrete Mathematics in Computer Science. --- Data Structures. --- 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 --- Algorism --- Algebra --- Arithmetic --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Informatics --- Science --- Mathematics --- Foundations --- Optical pattern recognition. --- Computer vision. --- Computer software. --- Computational complexity. --- Data structures (Computer scienc. --- Artificial Intelligence. --- Complexity, Computational --- Software, Computer --- Computer systems --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Pattern perception --- Perceptrons --- Visual discrimination --- Data structures (Computer science) --- Optical data processing. --- Computer science—Mathematics. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment