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Autor(en): 
  • Yu-Jin Zhang
  • 3-D Computer Vision: Principles, Algorithms and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Februar 2024  
    Genre:  EDV / Informatik 
     
    Bildverarbeitung / Computer Imaging, Vision, Pattern Recognition and Graphics / computer science / Computer Vision / Elektronik / Image processing / Image Recovery and Reconstruction / image understanding
    ISBN:  9789811975820 
    EAN-Code: 
    9789811975820 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 25 mm 
    Gewicht:  698 gr 
    Seiten:  448 
    Illustration:  XIII, 448 p. 1 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This textbook offers advanced content on computer vision (basic content can be found in its prerequisite textbook, "2D Computer Vision: Principles, Algorithms and Applications"), including the basic principles, typical methods and practical techniques. It is intended for graduate courses on related topics, e.g. Computer Vision, 3-D Computer Vision, Graphics, Artificial Intelligence, etc. The book is mainly based on my lecture notes for several undergraduate and graduate classes I have offered over the past several years, while a number of topics stem from my research publications co-authored with my students. This book takes into account the needs of learners with various professional backgrounds, as well as those of self-learners. Furthermore, it can be used as a reference guide for practitioners and professionals in related fields. To aid in comprehension, the book includes a wealth of self-test questions (with hints and answers). On the one hand, these questions help teachers to carry out online teaching and interact with students during lectures; on the other, self-learners can use them to assess whether they have grasped the key content.

      



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