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Titlebook: Semantic Multimedia; Third International David Duke,Lynda Hardman,Steffen Staab Conference proceedings 2008 Springer-Verlag Berlin Heidelb

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Liang Bai,Songyang Lao,Alan F. Smeaton,Noel E. O’Connorvents can terminate reproductive outputs from these habitats over multiple years which can affect local and downstream population replenishment. Due to impacts on nearshore hardbottom and coral resources, federal, state, and local agencies manage permitting provisions within state and federal laws w
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Onur Kucuktunc,Sare G. Sevil,A. Burak Tosun,Hilal Zitouni,Pinar Duygulu,Fazli Cant hawksbill turtles are mostly observed in South Florida waters (Jupiter and further south) on both nearshore and offshore reefs. Kemp’s ridley turtles are infrequently sighted but there is evidence that supports use of hardbottom reefs. All four of these species found on nearshore reefs in Florida
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Gorka Marcos,Petra Krämer,Arantza Illarramendi,Igor García,Julián Flórezd polycrystalline films are used, investigations on how to influence the thin film growth morphology in homoepitaxy uncover the means supplied by growth kinetics towards the goal of creating thin film interfaces with purposely defined morphological properties.
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Carsten Saathoff,Marcin Grzegorzek,Steffen Staabd polycrystalline films are used, investigations on how to influence the thin film growth morphology in homoepitaxy uncover the means supplied by growth kinetics towards the goal of creating thin film interfaces with purposely defined morphological properties.
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Automatic Summarization of Rushes Video Using Bipartite Graphs, in the TRECVID video summarization task in 2007 but with our own assessors. Results show that our approach leads to a significant improvement in terms of the fraction of the TRECVID summary ground truth included and is competitive with other approaches in TRECVID 2007.
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Validating the Detection of Everyday Concepts in Visual Lifelogs,bability of a concept’s presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were then evaluated on a subset of 95,907 images, to determine the precision for detection of each semantic concept and to draw
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