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Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval.This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001).

Computer vision --- Optical pattern recognition --- Markov processes. --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Stochastic processes --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Mathematical models.

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This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Co

Optical pattern recognition. --- Writing --- Interactive whiteboards. --- Image processing --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Digital image processing --- Digital electronics --- Computer input-output equipment --- Whiteboards --- Chirography --- Handwriting --- Language and languages --- Ciphers --- Penmanship --- Data processing. --- Digital techniques.

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This book is concerned with a fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs. It aims at condensing the high representational power of graphs into a computationally efficient and mathematically convenient feature vector. This volume utilizes the dissimilarity space representation originally proposed by Duin and Pekalska to embed graphs in real vector spaces. Such an embedding gives one access to all algorithms developed in the past for feature vectors, which has been the predominant representation formalism in pattern recognition and r

Vector spaces. --- Cluster theory (Nuclear physics)

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A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.

Pattern recognition systems --- Computer vision --- Reconnaissance des formes (Informatique) --- Vision par ordinateur --- Civil Engineering --- Electrical Engineering --- Applied Mathematics --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Electrical & Computer Engineering --- Computer vision. --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Machine vision --- Vision, Computer --- Engineering. --- Artificial intelligence. --- Computer graphics. --- Pattern recognition. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Pattern Recognition. --- Artificial Intelligence (incl. Robotics). --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Applications of Mathematics. --- Pattern perception --- Artificial intelligence --- Image processing --- Optical pattern recognition. --- Mathematics. --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Math --- Science --- 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 --- Optical data processing --- Perceptrons --- Visual discrimination --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Optical equipment

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An inadequate infrastructure for software testing is causing major losses to the world economy. The characteristics of software quality problems are quite similar to other tasks successfully tackled by artificial intelligence techniques. The aims of this book are to present state-of-the-art applications of artificial intelligence and data mining methods to quality assurance of complex software systems, and to encourage further research in this important and challenging area.
Contents:

• Fuzzy Cause-Effect Models of Software Testing (W Pedrycz & G Vukovich)
• Black

Computer software --- Artificial intelligence. --- 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 --- Software, Computer --- Computer systems --- Testing. --- Quality control.