This course, Introduction to Computer Vision, is designed to introduce the audience to the fundamentals of computer vision. It will cover topics such as camera model, calibration, epipolar geometry, object and texture representation, light and shading, colour, and the use of CNNs for object detection/classification and depth estimation. Prerequisites include basic calculus, linear algebra, probability and statistics, and some programming skills. Industry support includes Samsung, Qualcomm, LG, TI, Google, Microsoft, Amazon, Facebook and many more.
Learn Computer Vision with OpenCV Library using Python
3.7
Udemy32,299 learners
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This free course teaches students how to use the OpenCV library with Python to build a face detection program. Gain the skills to develop computer vision applications with OpenCV.
Computer Vision For iOS Developers Course
4.0
Udemy0 learners
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This course provides iOS developers with the skills to train and integrate Object Detection and Semantic Segmentation models into their apps, allowing them to leverage the power of computer vision.
Computer Vision with Embedded Machine Learning
2.5
Coursera0 learners
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This course explores the field of Computer Vision (CV) and how it can be used to automate the process of assigning meaning to digital images or videos. It covers the use of Machine Learning (ML) algorithms and techniques to accomplish CV tasks, and how these techniques can be deployed to embedded systems.
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