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Moments and Moment Invariants in Pattern Recognition

Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing;

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Invariants For Pattern Recognition And Classification

of Pattern Recognition and Artificial Intelligence (December 1999). The papers in this book are extended versions of the original material published;

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Data Complexity in Pattern Recognition

algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations;

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Data Complexity in Pattern Recognition

algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations;

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Perspectives on Pattern Recognition

Pattern recognition involves tasks such as pattern identification, feature extraction from them and pattern classification in categories;

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Computational Intelligence Paradigms in Advanced Pattern Classification

This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting;

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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image;

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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image;

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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

, feature or instance selection for classification, image analysis and retrieval, signals analysis and processing, applications of pattern;

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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

language; document processing and recognition; feature extraction, clustering and classification; pattern recognition and machine learning; neural;

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Computer Recognition Systems 2

of pattern recognition. The contributions cover all topics in pattern recognition including, for example, classification and interpretation of text;

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Pattern Classification

PATTERN CLASSIFICATION a unified view of statistical and neural approaches The product of years of research and practical experience;

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Image Processing and Pattern Recognition

Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech;

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Progress in Pattern Recognition Image Analysis Computer Vision and Applicatio

in topical sections on applications on pattern recognition; biometrics; computer vision; gesture recognition; image classification and retrieval;

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Computational Intelligence for Pattern Recognition

The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and;

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Advantages and Pitfalls of Pattern Recognition

Advantages and Pitfalls of Pattern Recognition presents various methods of pattern recognition and classification, useful to;

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Random Graphs for Statistical Pattern Recognition

resource presents: a detailed look at the application of random graphs to pattern recognition; extensive examples of applications of the graphs;

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Structural, Syntactic, and Statistical Pattern Recognition

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition;

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Pattern Recognition Techniques Applied to Biomedical Problems

several problems of classification, with a special focus on-but not limited to-pattern recognition modeling of biomedical signals and images;

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Video Analytics. Face and Facial Expression Recognition

, and the Second International Workshop on Deep Learning for Pattern Recognition, DLPR 2018, held at the 24th International Conference on;

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Machine Learning and Data Mining in Pattern Recognition

from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific;

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Machine Learning and Data Mining in Pattern Recognition

submissions. The papers cover the topics ranging from theoretical topics for classification, clustering, association rule and pattern mining to;

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Machine Learning and Data Mining in Pattern Recognition

169 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data;

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Machine Learning and Data Mining in Pattern Recognition

. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods;

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Structural, Syntactic, and Statistical Pattern Recognition

from 81 submissions. The accepted papers cover the major topics of current interest in pattern recognition, including classification and;

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Computational Intelligence in Multi Feature Visual Pattern Recognition

intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area;

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Auditory and Visual Pattern Recognition

in depth before addressing the more complex problems of pattern recognition and classification. This extensive and impressive research effort built;

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