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NVIDIA Adds GPU Acceleration for OpenCV Application Development

NVIDIA Adds GPU Acceleration for OpenCV Application Development

drugs and alcohol essays NVIDIA today announced CUDA support for OpenCV, the popular Computer Vision library used in developing advanced applications for the robotics, automotive, medical, consumer, security, manufacturing, and research fields. fiction essay

online dissertation and thesis etd With the addition of GPU acceleration to OpenCV, developers can run more accurate and sophisticated OpenCV algorithms in real-time on higher-resolution images while consuming less power. This will facilitate the development of scores of new, mainstream Computer Vision applications.

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action research dissertation report on education With thousands of developers and well over two million downloads to date, OpenCV is a popular Computer Vision library for the development of computational-intensive and powerful applications, many of which require robust real-time performance. For example, the new OpenCV depth calculation engine performs 5-10 times faster with GPU acceleration than with the equivalent CPU-only implementation. show my homework richard lander

thesis sentence writer “Computational power in Computer Vision has been a limiting factor not only for the use of recent powerful algorithms in object recognition, tracking and 3D reconstruction, but also has limited the creativity of algorithms people are willing to invent,” said Gary Bradski, senior researcher at Willow Garage, and founder of OpenCV. “With CUDA GPU acceleration, many OpenCV algorithms will run five to ten times faster, making current algorithms more practical for application developers and allowing the invention and combination of more capable applications in the future.”

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