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Record Nr. |
UNINA9910254221003321 |
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Autore |
Schauerte Boris |
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Titolo |
Multimodal Computational Attention for Scene Understanding and Robotics [[electronic resource] /] / 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 recognition |
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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