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Technical Articles

The Internet of Things, the interconnection of uniquely identifiable embedded computing devices, is a key vision processing opportunity.

Adding vision-processing capabilities to wearable systems both enhances existing product categories and fundamentally enables new categories

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Innovative semiconductor architectures are emerging to provide powerful, low-power image capture and knowledge extraction capabilities.

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Vision is rapidly emerging in the automotive market and, fused with other sensor technologies, is improving the safety of vehicles.

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Signs that see and understand the actions and characteristics of individuals in front of them can deliver numerous benefits.

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

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

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

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Cameras located in a vehicle's interior, coupled with cost-effective and power-efficient processors, can deliver abundant occupant benefits.

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Computer Vision Metrics: Chapter Eight (Part F)

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This is Part E of Chapter 8 of "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 8 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 8 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 8 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 8 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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Machine Learning (ML) has its origins in the field of artificial intelligence, and has now become a pervasive technology, says NVIDIA.

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This article from Altera look at trends impacting ADAS system-level design and new approaches for delivering production applications.

This is Part C of Chapter 7 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.

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