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1. |
Record Nr. |
UNINA9910376028903321 |
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Autore |
Angelides Marios |
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Titolo |
MUM 2010 : proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia, December 1-3, 2010, Limassol, Cyprus |
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Pubbl/distr/stampa |
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[Place of publication not identified], : ACM, 2010 |
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Descrizione fisica |
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1 online resource (239 pages) |
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Collana |
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Soggetti |
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Electrical & Computer Engineering |
Engineering & Applied Sciences |
Telecommunications |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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2. |
Record Nr. |
UNINA9910254221003321 |
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Autore |
Schauerte Boris |
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Titolo |
Multimodal Computational Attention for Scene Understanding and Robotics / / by Boris Schauerte |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XXIV, 203 p. 55 illus., 51 illus. in color.) |
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Collana |
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Cognitive Systems Monographs, , 1867-4925 ; ; 30 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Robotics |
Automation |
Artificial intelligence |
Optical data processing |
Pattern perception |
Computational Intelligence |
Robotics and Automation |
Artificial Intelligence |
Image Processing and Computer Vision |
Pattern Recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview. |
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Sommario/riassunto |
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This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. |
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In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated. . |
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