Machine Learning Techniques Applied to Evaluating Picture Quality
Karl Kuhn
Tektronix
Karl Kuhn launched his career at Tektronix in 2000. Prior to Tektronix he was the lead Video Test Engineer for IBM in their Digital Video Development Laboratory in Bethesda, MD. Karl holds 3 U.S. patents and 1 Japanese patent that cover In-service Testing of Digital Broadcast Video. He is a contributing author for the 11th Edition of the NAB Handbook responsible for chapter 2.9 covering Digital Video Standards and Practices. He is the Past SMPTE Eastern Region Governor and now SMPTE North American Sections Director. In 2015 Karl was raised to SMPTE Fellow. He is also a Certified Project Management Professional thru PMI and the George Washington University.
Abstract
This paper is a tutorial on how to apply Machine Learning to evaluate picture quality measurement and scoring. Traditionally this has been done using full reference techniques that involve comparing test images with reference... [ view full abstract ]
Authors
- Karl Kuhn (Organisation: Tektronix, Job Title: -, Speaker Consent and Release: -)
Topic Area
Possible Topics: Trends & Future Tech
Session
F1130-GBB » Machine Learning Techniques Applied to Evaluating Picture Quality (11:30 - Friday, 6th April, Grand Ballroom B)
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