Computer vision fundamentals

• Titel: Computer vision fundamentals
• Titelzusatz: implementing computer vision techniques using deep learning
• Mitwirkende: Alake, Richmond [MitwirkendeR]
• Institutionen: O'Reilly (Firm), [Verlag]
• Ausgabe: [First edition].
• Verlagsort: [Sebastopol, California]
• Verlag: O'Reilly Media, Inc.
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: 1 online resource (1 video file (3 hr., 29 min.))
• Illustrationen: sound, color.
• Fussnoten: Online resource; title from title details screen (O’Reilly, viewed October 28, 2024)
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Vision par ordinateur
• Sach-SW: Apprentissage profond
• Sach-SW: Instructional films
• Sach-SW: Nonfiction films
• Sach-SW: Internet videos
• Sach-SW: Films de formation
• Sach-SW: Films autres que de fiction
• Sach-SW: Vidéos sur Internet
• K10plus-PPN: 1910507520
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4629551107
• Lokale URL Inst.: Zum Volltext

Abstract

This course is an extensive exploration of how artificial intelligence is driving significant advances in the field of computer vision. This course melds theory and practice, introducing everything from the foundational aspects of image processing to the hands-on implementation of advanced deep learning models in PyTorch, including applications on edge devices. In a progressively digital and data-driven world, processing, analyzing, and deriving insights from vast quantities of visual data is crucial. This course will provide you with the requisite skills and knowledge to apply computer vision techniques to a wide array of sectors, such as autonomous vehicles, facial recognition systems, medical imaging, and edge computing. By the end of this course, you will have a well-rounded understanding of the fundamental concepts and practical applications of computer vision and deep learning. You will be equipped with the tools and knowledge to implement these models and solve real-world problems, giving you a competitive advantage in your software development or data science career.