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Computer Vision ACCV 2018 Workshops: 14th Asian Conference on Computer Vision, Perth, Australia, December 26, 2018, Revised Selected Papers 2019 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 541 pages, kõrgus x laius: 235x155 mm, kaal: 848 g, 230 Illustrations, color; 30 Illustrations, black and white; XV, 541 p. 260 illus., 230 illus. in color., 1 Paperback / softback
  • Sari: Image Processing, Computer Vision, Pattern Recognition, and Graphics 11367
  • Ilmumisaeg: 19-Jun-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030210731
  • ISBN-13: 9783030210731
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Computer Vision ACCV 2018 Workshops: 14th Asian Conference on Computer Vision, Perth, Australia, December 26, 2018, Revised Selected Papers 2019 ed.Suurem pilt
  • Formaat: Paperback / softback, 541 pages, kõrgus x laius: 235x155 mm, kaal: 848 g, 230 Illustrations, color; 30 Illustrations, black and white; XV, 541 p. 260 illus., 230 illus. in color., 1 Paperback / softback
  • Sari: Image Processing, Computer Vision, Pattern Recognition, and Graphics 11367
  • Ilmumisaeg: 19-Jun-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030210731
  • ISBN-13: 9783030210731
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030210731.html
Märksõnad:
This LNCS workshop proceedings, ACCV 2018, contains carefully reviewed and selected papers from 11 workshops, each having 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).
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).