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Machine Learning in Computer Vision: Computational Imaging and Vision 29

Dominic Simmons

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Machine learning is a subfield of artificial intelligence that gives computers the ability to learn without being explicitly programmed. In computer vision, machine learning is used to train computers to identify and interpret images. This technology has a wide range of applications, including medical imaging, autonomous driving, and object recognition.

Machine Learning in Computer Vision (Computational Imaging and Vision 29)

Machine Learning in Computer Vision (Computational Imaging and Vision Book 29)

by Virginia E. Gray

4 out of 5

Language	:	English
File size	:	3536 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Print length	:	242 pages

Computational Imaging

Computational imaging is a field of computer vision that uses machine learning to improve the quality of images. Computational imaging techniques can be used to remove noise from images, enhance contrast, and correct for distortions. These techniques can be used to improve the quality of images for a variety of applications, including medical imaging, remote sensing, and surveillance.

Computer Vision 29

Computer Vision 29 is a course at the University of California, Berkeley that covers the basics of computer vision. The course covers topics such as image formation, image processing, feature extraction, and object recognition. The course also introduces students to the use of machine learning in computer vision.

Machine Learning in Computer Vision Applications

Machine learning is used in a wide range of computer vision applications, including:

Medical imaging: Machine learning is used to analyze medical images to diagnose diseases, plan treatments, and monitor patient progress.
Autonomous driving: Machine learning is used to train computers to drive cars autonomously. This technology is used in self-driving cars, which are able to navigate roads without human input.
Object recognition: Machine learning is used to train computers to recognize objects in images. This technology is used in a variety of applications, including facial recognition, object tracking, and industrial inspection.

Machine learning is a powerful tool that is transforming the field of computer vision. Machine learning techniques can be used to improve the quality of images, train computers to identify and interpret images, and develop new computer vision applications. As machine learning continues to develop, it is likely to have an even greater impact on the field of computer vision in the years to come.

Machine Learning in Computer Vision (Computational Imaging and Vision Book 29)

by Virginia E. Gray

4 out of 5