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This is the bibliography for "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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This is Part D of Chapter 1 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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This is Part C of Chapter 1 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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This is Part B of Chapter 1 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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This is Part A of Chapter 1 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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This is the introduction to "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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Post-capture image processing can now take place near-immediately on a mobile electronics device, thanks to embedded vision technology.

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Vision processors, fed by image sensors and running robust software, are transforming industrial automation aspirations into reality.

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Fast, low power processors and high resolution, high frame rate image sensors, along with powerful software, bring AR to the masses.

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ADAS is among the early success stories in the burgeoning embedded vision era, and its usage is rapidly expanding.

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