Adaptive Multimedia Retrieval Context Exploration And Fusion
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Adaptive Multimedia Retrieval. Context, Exploration and Fusion by Marcin Detyniecki,Peter Knees,Andreas Nürnberger,Markus Schedl,Sebastian Stober Pdf
This book constitutes the refereed proceedings of the 8th International Conference on Adaptive Multimedia Retrieval, AMR 2010, held in Linz, Austria, in August 2010. The 14 revised full papers and the invited contribution presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Context-based personalization; media information fusion; video retrieval; audio and music retrieval; adaptive similarities; and finding and organizing.
Adaptive Multimedia Retrieval. Context, Exploration and Fusion by Marcin Detyniecki,Peter Knees,Andreas Nürnberger,Markus Schedl,Sebastian Stober Pdf
This book constitutes the refereed proceedings of the 8th International Conference on Adaptive Multimedia Retrieval, AMR 2010, held in Linz, Austria, in August 2010. The 14 revised full papers and the invited contribution presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Context-based personalization; media information fusion; video retrieval; audio and music retrieval; adaptive similarities; and finding and organizing.
Adaptive Multimedia Retrieval:User, Context, and Feedback by Stéphane Marchand-Maillet,Eric Bruno,Andreas Nürnberger,Marcin Detyniecki Pdf
This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Adaptive Multimedia Retrieval, AMR 2006, held in Geneva, Switzerland in July 2006. The papers cover ontology-based retrieval and annotation, ranking and similarity measurements, music information retrieval, visual modeling, adaptive retrieval, structuring multimedia, as well as user integration and profiling.
Adaptive Multimedia Retrieval: User, Context, and Feedback by Marcin Detyniecki,Joemon M. Jose,Andreas Nürnberger,C. J. van Rijsbergen Pdf
This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Adaptive Multimedia Retrieval, held in September 2005. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement. Also included are three invited papers by leading researchers in the area to illustrate the core topics of the workshop: User, Context and Feedback. The papers are organized in topical sections on ranking, systems, spatio-temporal relations, using feedback, using context, and meta data.
Adaptive Multimedia Retrieval: Retrieval, User, and Semantics by Nozha Boujemaa,Marcin Detyniecki,Andreas Nürnberger Pdf
This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Adaptive Multimedia Retrieval, AMR 2007, held in Paris, France, in July 2007. The 18 revised full papers presented together with 2 invited papers were carefully selected during two rounds of reviewing and improvement. The papers are organized in topical sections on image annotation, feedback and user modelling, music retrieval, fusion, P2P and middleware, databases and summarization, as well as ontology and semantics.
Adaptive Multimedia Retrieval:User, Context, and Feedback by Stéphane Marchand-Maillet,Eric Bruno,Andreas Nürnberger,Marcin Detyniecki Pdf
This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Adaptive Multimedia Retrieval, AMR 2006, held in Geneva, Switzerland in July 2006. The papers cover ontology-based retrieval and annotation, ranking and similarity measurements, music information retrieval, visual modeling, adaptive retrieval, structuring multimedia, as well as user integration and profiling.
Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation by Andreas Nürnberger,Sebastian Stober,Birger Larsen,Marcin Detyniecki Pdf
This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Adaptive Multimedia Retrieval, AMR 2012, held in Copenhagen, Denmark, in October 2012. The 17 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers cover topics of state of the art contributions, features and classification, location context, language and semantics, music retrieval, and adaption and HCI.
Smart Algorithms for Multimedia and Imaging by Michael N. Rychagov,Ekaterina V. Tolstaya,Mikhail Y. Sirotenko Pdf
This book presents prospective, industrially proven methods and software solutions for storing, processing, and viewing multimedia content on digital cameras, camcorders, TV, and mobile devices. Most of the algorithms described here are implemented as systems on chip firmware or as software products and have low computational complexity and memory consumption. In the four parts of the book, which contains a total of 16 chapters, the authors address solutions for the conversion of images and videos by super-resolution, depth estimation and control and mono-to-stereo (2D to 3D) conversion; display applications by video editing; the real-time detection of sport episodes; and the generation and reproduction of natural effects. The practical principles of machine learning are illustrated using technologies such as image classification as a service, mobile user profiling, and automatic view planning with dictionary-based compressed sensing in magnetic resonance imaging. The implementation of these technologies in mobile devices is discussed in relation to algorithms using a depth camera based on a colour-coded aperture, the animated graphical abstract of an image, a motion photo, and approaches and methods for iris recognition on mobile platforms. The book reflects the authors’ practical experience in the development of algorithms for industrial R&D and the commercialization of technologies. Explains digital techniques for digital cameras, camcorders, TV, mobile devices; Offers essential algorithms for the processing pipeline in multimedia devices and accompanying software tools; Features advanced topics on data processing, addressing current technology challenges.
Media, Materiality and Memory by Elodie A. Roy Pdf
Media, Materiality and Memory: Grounding the Groove examines the entwinement of material music objects, technology and memory in relation to a range of independent record labels, including Sarah Records, Ghost Box and Finders Keepers. Moving from Edison’s phonograph to digital music files, from record collections to online archives, Roy argues that materiality plays a crucial role in constructing and understanding the territory of recorded sound. How do musical objects ‘write’ cultural narratives? How can we unearth and reactivate past histories by looking at yesterday’s media formats? What is the nature, and fate, of the physical archive in an increasingly dematerialized world? In what ways do physical and digital musical objects coexist and intersect? With its innovative theoretical approach, the book explores the implications of materialization in the fashioning of a musical world and its cultural transmission. A substantial contribution to the field of music and material culture studies, Media, Materiality and Memory also provides a nuanced and timely reflection on nostalgia and forgetting in the digital age.
An Introduction to Audio Content Analysis by Alexander Lerch Pdf
An Introduction to Audio Content Analysis Enables readers to understand the algorithmic analysis of musical audio signals with AI-driven approaches An Introduction to Audio Content Analysis serves as a comprehensive guide on audio content analysis explaining how signal processing and machine learning approaches can be utilized for the extraction of musical content from audio. It gives readers the algorithmic understanding to teach a computer to interpret music signals and thus allows for the design of tools for interacting with music. The work ties together topics from audio signal processing and machine learning, showing how to use audio content analysis to pick up musical characteristics automatically. A multitude of audio content analysis tasks related to the extraction of tonal, temporal, timbral, and intensity-related characteristics of the music signal are presented. Each task is introduced from both a musical and a technical perspective, detailing the algorithmic approach as well as providing practical guidance on implementation details and evaluation. To aid in reader comprehension, each task description begins with a short introduction to the most important musical and perceptual characteristics of the covered topic, followed by a detailed algorithmic model and its evaluation, and concluded with questions and exercises. For the interested reader, updated supplemental materials are provided via an accompanying website. Written by a well-known expert in the music industry, sample topics covered in Introduction to Audio Content Analysis include: Digital audio signals and their representation, common time-frequency transforms, audio features Pitch and fundamental frequency detection, key and chord Representation of dynamics in music and intensity-related features Beat histograms, onset and tempo detection, beat histograms, and detection of structure in music, and sequence alignment Audio fingerprinting, musical genre, mood, and instrument classification An invaluable guide for newcomers to audio signal processing and industry experts alike, An Introduction to Audio Content Analysis covers a wide range of introductory topics pertaining to music information retrieval and machine listening, allowing students and researchers to quickly gain core holistic knowledge in audio analysis and dig deeper into specific aspects of the field with the help of a large amount of references.
Recommender System based on linked Data by Figueroa, Cristhian,Corrales, Juan Carlos,Morisio, Maurizio Pdf
Linked Data principles have led to semantically interlink and connect different resourcesat data level regardless the structure, authoring, location etc. Data available on the Web using Linked Data has resulted in a global data space called the Web of Data. Moreover, thanks to the efforts of the scientific community and the W3C Linked Open Data (LOD) project, more and more data have been published on the Web of Data, helping its growth and evolution. This book studies Recommender Systems that use LInked Data as a source for generating recommendations exploiting the large amount of available resources and the relationships between them. Firts, a comprehensive state of the art is preseted in order to indetify and study frameworks and algorithms for RS that rely on Linked Data. Second a framework named AlLied taht makes available implementations of the most used algortihms for resource recommendation based on Linked Data is described. This framework is inteded to use and test the recommendation algorithms in various domains and contexts, and to analyze their behavior under different conditions. Accordingly the framework is suitable to compare the results of these algorithms both in performance and relevance, and to enable the development of innovative applications on top of it.
Adaptive Multimedia Retrieval. Understanding Media and Adapting to the User by Marcin Detyniecki,Ana García-Serrano,Andreas Nürnberger Pdf
This book constitutes the refereed proceedings of the 7th International Conference on Adaptive Multimedia Retrieval, AMR 2009, held in Madrid, Spain, in September 2009. The 12 revised full papers and the invited contribution presented were carefully reviewed. The papers are organized in topical sections on grasping multimedia streams; pinpointing music; adapting distances; understanding images; and around the user.
Adaptive Multimedia Retrieval: Identifying, Summarizing, and Recommending Image and Music by Marcin Detyniecki,Ulrich Leiner,Andreas Nürnberger Pdf
This volume constitutes the refereed proceedings of the 6th International Workshop on Adaptive Multimedia Retrieval, AMR 2008, held in Berlin, Germany, in June 2008.
Machine Learning Techniques for Adaptive Multimedia Retrieval by Chia-Hung Wei,Yue Li Pdf
"This book disseminates current information on multimedia retrieval, advancing the field of multimedia databases, and educating the multimedia database community on machine learning techniques for adaptive multimedia retrieval research, design and applications"--Provided by publisher.
