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|a 9783319337968
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|a 10.1007/978-3-319-33796-8
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|a Schauerte, Boris.
|e author.
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|a Multimodal Computational Attention for Scene Understanding and Robotics
|h [electronic resource] /
|c by Boris Schauerte.
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|a 1st ed. 2016.
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264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
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300 |
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|a XXIV, 203 p. 55 illus., 51 illus. in color.
|b online resource.
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|a Cognitive Systems Monographs,
|x 1867-4925 ;
|v 30
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490 |
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|a Springer eBook Collection
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|a Introduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.
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|a 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. 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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|a Loaded electronically.
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|a Electronic access restricted to members of the Holy Cross Community.
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|a Computational intelligence.
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|a Robotics.
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650 |
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|a Automation.
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650 |
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|a Artificial intelligence.
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650 |
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|a Optical data processing.
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|a Pattern recognition.
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|a Electronic resources (E-books)
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