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First Principles of Computer Vision

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First Principles of Computer Vision provided by Coursera is a comprehensive online course, which lasts for 30 weeks long, 2 hours a week. First Principles of Computer Vision is taught by Shree Nayar. Upon completion of the course, you can receive an e-certificate from Coursera. The course is taught in Englishand is Paid Course. Visit the course page at Coursera for detailed price information.

Columbia University via Coursera
30 weeks long, 2 hours a week
27th, Oct 2022
Overview

  • This specialization presents the first comprehensive treatment of the foundations of computer vision. It focuses on the mathematical and physical underpinnings of vision and has been designed for learners, practitioners and researchers who have little or no knowledge of computer vision. The program includes a series of 5 courses. Any learner who completes this specialization has the potential to build a successful career in computer vision, a thriving field that is expected to increase in importance in the coming decades.

Syllabus

  • Course 1: Camera and Imaging
    - Offered by Columbia University. This course covers the fundamentals of imaging – the creation of an image that is ready for consumption or ... Enroll for free.

    Course 2: Features and Boundaries
    - Offered by Columbia University. This course focuses on the detection of features and boundaries in images. Feature and boundary detection is ... Enroll for free.

    Course 3: 3D Reconstruction - Single Viewpoint
    - Offered by Columbia University. This course focuses on the recovery of the 3D structure of a scene from its 2D images. In particular, we are ... Enroll for free.

    Course 4: 3D Reconstruction - Multiple Viewpoints
    - Offered by Columbia University. This course focuses on the recovery of the 3D structure of a scene from images taken from different ... Enroll for free.

    Course 5: Visual Perception
    - Offered by Columbia University. The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image ... Enroll for free.

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