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Technologies

The listing below showcases the most recently published Embedded Vision Academy content associated with various embedded vision technologies. Reference the links on the right side of this page to access the full suite of technology-tailored embedded vision content, sorted by technology.

Algorithms

Elif Albuz of NVIDIA delivers a presentation at the December 2014 Embedded Vision Alliance Member Meeting.
Academy

Doug Johnston of Prism Skylabs delivers a presentation at the December 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

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

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

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

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

Dr. Ren Wu of Baidu delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

Mel Spiese of Cubic delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

Scott Krig, the author of "Computer Vision Metrics," delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

Matt Bell of Matterport delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

Computer Vision Metrics: Chapter Eight (Part F)
Academy

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

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

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

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

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

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

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

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

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

Linley Gwennap of the Linley Group delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

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

Dr. Ren Wu of Baidu delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

Scott Krig, the author of "Computer Vision Metrics," delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

Computer Vision Metrics: Chapter Eight (Part F)
Academy

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

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

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

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

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

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

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

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

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

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

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

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

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

Matt Bell of Matterport delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

Computer Vision Metrics: Chapter Eight (Part F)
Academy

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

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

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

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

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

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

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

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

Elif Albuz of NVIDIA delivers a presentation at the December 2014 Embedded Vision Alliance Member Meeting.
Academy

Doug Johnston of Prism Skylabs delivers a presentation at the December 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

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

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

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

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

Dr. Ren Wu of Baidu delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

Scott Krig, the author of "Computer Vision Metrics," delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

Matt Bell of Matterport delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

Computer Vision Metrics: Chapter Eight (Part F)
Academy

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

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

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

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

Elif Albuz of NVIDIA delivers a presentation at the December 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

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

Scott Krig, the author of "Computer Vision Metrics," delivers a presentation at the September 2014 Embedded Vision Alliance Member Meeting.
Academy

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

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

Computer Vision Metrics: Chapter Eight (Part F)
Academy

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

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

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

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

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

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

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

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

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

This is Part H of Chapter 6 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.
Academy

This is Part G of Chapter 6 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.
Academy

This is Part F of Chapter 6 of "Computer Vision Metrics: Survey, Taxonomy, and Analysis," written by Scott Krig and published by Apress.
Academy