开始时间: 04/22/2022 持续时间: 未知
所在平台: CourseraArchive 课程类别: 计算机科学 |
课程主页: https://www.coursera.org/course/vision
课程评论:没有评论
Computer vision seeks to develop algorithms that replicate one of the most amazing capabilities of the human brain - inferring properties of the external world purely by means of the light reflected from various objects to the eyes. We can determine how far away these objects are, how they are oriented with respect to us, and in relationship to various other objects. We reliably guess their colors and textures, and we can recognize them - this is a chair, this is my dog Fido, this is a picture of Bill Clinton smiling. We can segment out regions of space corresponding to particular objects and track them over time, such as a basketball player weaving through the court.
In this course, we will study the concepts and algorithms behind some of the remarkable successes of computer vision - capabilities such as face detection, handwritten digit recognition, reconstructing three-dimensional models of cities, automated monitoring of activities, segmenting out organs or tissues in biological images, and sensing for control of robots. We will build this up from fundamentals - an understanding of the geometry and radiometry of image formation, core image processing operations, as well as tools from statistical machine learning. On completing this course a student would understand the key ideas behind the leading techniques for the main problems of computer vision - reconstruction, recognition and segmentation - and have a sense of what computers today can or cannot do.
In this course, we will study the concepts and algorithms behind some of the remarkable successes of computer vision - capabilities such as face detection, handwritten digit recognition, reconstructing three-dimensional models of cities and more.
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