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Record Nr. |
UNISA996466287503316 |
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Titolo |
Computer Vision – ACCV 2018 Workshops [[electronic resource] ] : 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers / / edited by Gustavo Carneiro, Shaodi You |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (XV, 541 p. 260 illus., 230 illus. in color.) |
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Collana |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 11367 |
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Disciplina |
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Soggetti |
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Optical data processing |
Artificial intelligence |
Computer organization |
Computer hardware |
Image Processing and Computer Vision |
Artificial Intelligence |
Computer Systems Organization and Communication Networks |
Computer Hardware |
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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 and index. |
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Nota di contenuto |
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Scene Understanding and Modelling (SUMO) Challenge -- Learning and Inference Methods for High Performance Imaging (LIMHPI) -- Attention/Intention Understanding (AIU) -- Museum Exhibit Identification Challenge (Open MIC) for Domain Adaptation and Few-Shot Learning -- RGB-D - Sensing and Understanding via Combined Colour and Depth -- Dense 3D Reconstruction for Dynamic Scenes -- AI Aesthetics in Art and Media (AIAM) -- Robust Reading (IWRR), Artificial Intelligence for Retinal Image Analysis (AIRIA) -- Combining Vision and Language, Advanced Machine Vision for Real-life and Industrially Relevant Applications (AMV). |
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Sommario/riassunto |
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This LNCS workshop proceedings, ACCV 2018, contains carefully reviewed and selected papers from 11 workshops, each having |
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different types or programs: Scene Understanding and Modelling (SUMO) Challenge, Learning and Inference Methods for High Performance Imaging (LIMHPI), Attention/Intention Understanding (AIU), Museum Exhibit Identification Challenge (Open MIC) for Domain Adaptation and Few-Shot Learning, RGB-D - Sensing and Understanding via Combined Colour and Depth, Dense 3D Reconstruction for Dynamic Scenes, AI Aesthetics in Art and Media (AIAM), Robust Reading (IWRR), Artificial Intelligence for Retinal Image Analysis (AIRIA), Combining Vision and Language, Advanced Machine Vision for Real-life and Industrially Relevant Applications (AMV). |
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