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Introduction to Pattern Recognition
Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. - Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition - Solved examples in Matlab, including real-life data sets in imaging and audio recognition - Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)
Introduction to Audio Analysis
Introduction to Audio Analysis serves as a standalone introduction to audio analysis, providing theoretical background to many state-of-the-art techniques. It covers the essential theory necessary to develop audio engineering applications, but also uses programming techniques, notably MATLAB®, to take a more applied approach to the topic. Basic theory and reproducible experiments are combined to demonstrate theoretical concepts from a practical point of view and provide a solid foundation in the field of audio analysis. Audio feature extraction, audio classification, audio segmentation, and music information retrieval are all addressed in detail, along with material on basic audio processin...
Multimedia Services in Intelligent Environments
Multimedia services involve processing, transmission and retrieval of multiple forms of information. Multimedia services have gained momentum in the past few years due to the easy availability of computing power and storage media. Societyisdemandinghuman-likeintelligentbehaviour,suchasadaptationand generalization, from machines every day. With this view in mind, researchers are working on fusing intelligent paradigms such as arti?cial neural networks, swarm intelligence, arti?cial immune systems, evolutionary computing and multiagents with multimedia services. Arti?cial neural networks use neurons, interconnected using various schemes, for fusing learning in multimedia-based systems. Evoluti...
Affective Computing and Intelligent Interaction
The two-volume set LNCS 6974 and LNCS 6975 constitutes the refereed proceedings of the Fourth International Conference on Affective Computing and Intelligent Interaction, ACII 2011, held in Memphis,TN, USA, in October 2011. The 135 papers in this two volume set presented together with 3 invited talks were carefully reviewed and selected from 196 submissions. The papers are organized in topical sections on recognition and synthesis of human affect, affect-sensitive applications, methodological issues in affective computing, affective and social robotics, affective and behavioral interfaces, relevant insights from psychology, affective databases, Evaluation and annotation tools.
Music and Artificial Intelligence
This book constitutes the refereed proceedings of the Second International Conference on Music and Artificial Intelligence, ICMAI 2002, held in Edinburgh, Scotland, UK in September 2002.The 16 revised full papers presented together with abstracts of 2 invited talks were carefully reviewed and selected for inclusion in the proceedings. Among the topics addressed are parsing for music and language, patterns in music, musical pattern recognition, visualisation, sound classification, tonal structure representation, musical learning systems, pattern analysis, musical perception, melodic segmentation, and time series analysis.
Animation Production
This text follows the animation production by concentrating on the documentation necessary to accurately and professionally organize each step of the process. Examples of each piece of paperwork needed to complete the project will be shown. Many newcomers to the field are not experienced in the basic processes to organize their project in an orderly manner. The result is a chaotic, inefficient, and incomplete product. Readers are presented with a step-by-step guide to organizing the process by following professional standards in creating needed and useful documentation for all animators, whether creating in cells, stop-motion, experimental, or computer graphic productions. Key Features Provides simplified but intense coverage of animation production. Written to be easily read by newcomers to the field, ranging from students to professionals. Each chapter contains objectives, summaries, examples of forms, key terms, and examples of how professionals use the same techniques. This book provides both students and instructors an easily understandable explanation of the system and the directions on how to prepare documentation.
Web and Wireless Geographical Information Systems
The main topic of the W2GIS workshop is theoretical and technical issues of Web and wireless geographical information systems. This workshop followed the successful 2001, 2002 and 2003 editions, held in Kyoto, Singapore and Rome, respectively. The 2004 edition was held in Goyang, Korea.
Opportunistic Networking
Opportunistic networking, by definition, allows devices to communicate whenever a window of opportunity is available. Many emerging technologies employ opportunistic exchanges of information. This book addresses this trend in communications engineering, taking into account three specific areas—vehicular, device-to-device (D2D), and cognitive radio—while describing the opportunistic communication methods of each. From smart homes to smart cities, smart agriculture to never-die-networks and beyond, the text explores the state of the art of opportunistic networking, providing the latest research, developments, and practices in one concise source.
Machine Learning and Music Generation
Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.
