This 3rd edition tackles the basic principle of deep learning as well as the application of combination of wavelet theory with deep learning to pattern recognition. Five new chapters related to the combination of wavelet theory and deep learning are added with many novel research results.The useful reference text will benefit academics, researchers, computer scientists, electronic engineers and graduate students in the field of pattern recognition, image analysis, machine learning and electrical and electronic engineering.

The 2nd edition is an update of the book Wavelet Theory and its Application to Pattern Recognition published in 2000. Three new chapters, which are research results conducted during 2001-2008, are added. The book consists of three parts — the first presents a brief survey of the status of pattern recognition with wavelet theory; the second contains the basic theory of wavelet analysis; the third includes applications of wavelet theory to pattern recognition. The new book provides a bibliography of 170 references including the current state-of-the-art theory and applications of wavelet analysis to pattern recognition.

Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods and deep learning. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics and deep learning architectures. The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods. To complement the survey, the textbook includes useful analyses which provide insight into the goals of various methods, why they work, and how they may be optimized. The text delivers an essential survey and a valuable taxonomy, thus providing a key learning tool for students, researchers and engineers, to supplement the many effective hands-on resources and open source projects, such as OpenCV and other imaging and deep learning tools.

Intelligent Environments (IE) play an increasingly important role in many areas of our lives, including education, healthcare and the domestic environment. The term refers to physical spaces incorporating pervasive computing technology used to achieve specific goals for the user, the environment or both. This book presents the proceedings of the workshops of the 9th International Conference on Intelligent Environments (IE ‘13), held in Athens, Greece, in July 2013. The workshops which were presented in the context of this conference range from regular lectures to practical sessions. They provide a forum for scientists, researchers and engineers from both industry and academia to engage in discussions on newly emerging or rapidly evolving topics in the field. Topics covered in the workshops include artificial intelligence techniques for ambient intelligence; applications of affective computing in intelligent environments; smart offices and other workplaces; intelligent environment technology in education for creative learning; museums as intelligent environments; the application of intelligent environment technologies in the urban context for creating more sociable, intelligent cities and for constructing urban intelligence. IE can enrich user experience, better manage the environment’s resources, and increase user awareness of that environment. This book will be of interest to all those whose work involves the application of intelligent environments.

Pattern recognition, image processing and computer vision are closely linked areas which have seen enormous progress in the last fifty years. Their applications in our daily life, commerce and industry are growing even more rapidly than theoretical advances. Hence, the need for a new handbook in pattern recognition and computer vision every five or six years as envisioned in 1990 is fully justified and valid.The book consists of three parts: (1) Pattern recognition methods and applications; (2) Computer vision and image processing; and (3) Systems, architecture and technology. This book is intended to capture the major developments in pattern recognition and computer vision though it is impossible to cover all topics.The chapters are written by experts from many countries, fully reflecting the strong international research interests in the areas. This fifth edition will complement the previous four editions of the book.

With the recent and enormous increase in the amount of available data sets of all kinds, applying effective and efficient techniques for analyzing and extracting information from that data has become a crucial task. Intelligent Data Analysis for Real-Life Applications: Theory and Practice investigates the application of Intelligent Data Analysis (IDA) to these data sets through the design and development of algorithms and techniques to extract knowledge from databases. This pivotal reference explores practical applications of IDA, and it is essential for academic and research libraries as well as students, researchers, and educators in data analysis, application development, and database management.

This book constitutes the refereed proceedings of the 4th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2011, held in Moscow, Russia in June/July 2011. The 65 revised papers presented together with 5 invited talks were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on pattern recognition and machine learning; image analysis; image and video information retrieval; natural language processing and text and data mining; watermarking, steganography and biometrics; soft computing and applications; clustering and network analysis; bio and chemo analysis; and document image processing.

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This volume presents the 5th European Conference of the International Federation for Medical and Biological Engineering (EMBEC), held in Budapest, 14-18 September, 2011. The scientific discussion on the conference and in this conference proceedings include the following issues: - Signal & Image Processing - ICT - Clinical Engineering and Applications - Biomechanics and Fluid Biomechanics - Biomaterials and Tissue Repair - Innovations and Nanotechnology - Modeling and Simulation - Education and Professional

This is not a purely mathematical book. It presents the basic principle of wavelet theory to electrical and electronic engineers, computer scientists, and students, as well as the ideas of how wavelets can be applied to pattern recognition. It also contains many novel research results from the authors'' research team.