Computer Vision Specialization

开始时间: 04/22/2022 持续时间: Unknown

所在平台: Coursera专项课程

课程类别: 计算机科学

大学或机构: CourseraNew

课程主页: https://www.coursera.org/specializations/computervision

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课程详情

NOTE: This specialization is closing to new enrollments on December 4, 2019. Enroll prior to this date if you'd like to access content and earn a specialization certificate. This specialization provides a foundation in the rapidly expanding research field of computer vision, laying the groundwork necessary for designing sophisticated vision applications. Learners explore the integral elements that enable vision applications, ranging from editing images to reading traffic signs in self-driving cars to factory robots navigating around human co-workers. Content includes image processing and state-of-the-art vision techniques, augmented by insights from top leaders in the computer vision field. Learners gain hands-on experience writing computer vision programs through online labs using MATLAB and supporting toolboxes. The specialization is taught in MATLAB* using computer vision and supporting toolboxes. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). A free license to install MATLAB for the duration of the course is available from MathWorks.

课程大纲

Computer Vision Basics
Image Processing, Features & Segmentation
Stereo Vision, Dense Motion & Tracking
Visual Recognition & Understanding

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课程简介

纽约州立大学布法罗分校的计算机视觉专项课程(Computer Vision Specialization),这个专项系列包含4门子课程,涵盖计算机视觉基础,图像处理、特征和分割, 立体视觉、密集运动和跟踪,视觉识别与理解,感兴趣的同学可以关注:Learn how computers visually process the world. Dive into artificial intelligence’s fastest-growing field

课程标签

图像处理 计算机视觉基础 计算机视觉 图像特征 图像分割 立体视觉 密集运动和跟踪 视觉识别与理解

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