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Advanced computer vision projects

Author: Matthew Rever
Publisher: [Place of publication not identified] : Packt, [2018]
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"Python's wealth of powerful packages along with its clear syntax make state-of-the art computer vision and machine learning accessible to developers with a variety of backgrounds. This video course will equip you with the tools and skills to utilize the latest and greatest algorithms in computer vision, making applications that weren't possible until recent years. In this course, you'll continue to use TensorFlow  Read more...
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Details

Genre/Form: Instructional films
Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Matthew Rever
OCLC Number: 1056626491
Notes: Title from title screen (viewed October 10, 2018).
Date of publication from resource description page.
Performer(s): Presenter, Matthew Rever.
Description: 1 online resource (1 streaming video file (1 hr., 36 min., 38 sec.)) : digital, sound, color
Responsibility: Matthew Rever.

Abstract:

"Python's wealth of powerful packages along with its clear syntax make state-of-the art computer vision and machine learning accessible to developers with a variety of backgrounds. This video course will equip you with the tools and skills to utilize the latest and greatest algorithms in computer vision, making applications that weren't possible until recent years. In this course, you'll continue to use TensorFlow and extend it to generate full captions from images. Later, you'll see how to read text from license plates from real-world images using Google's Tesseract Software. Finally, you'll see how to track human body poses using "DeeperCut" within TensorFlow. At the end of this course, you'll develop an application that can estimate human poses within images and will be able to take on the world with best practices in computer vision with machine learning."--Resource description page.

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