Deep Learning in Aerial Systems Using Jetson

Features, Computer Vision, cuDNN, Deep Learning, Jetson

Nadeem Mohammad, posted Nov 03 2016

The adoption of unmanned aerial systems (UAS) has been steadily growing over the last decade. While UAS originated with military applications, they have proven to be beneficial in a variety of other fields including agriculture, geographical mapping, aerial photography, and search and rescue. These systems, however, require a person in the loop for remote control, […]

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NVIDIA VRWorks support for Unity

GameWorks, VRWorks, VR, Ansel

David Coombes, posted Nov 02 2016

Today NVIDIA and Unity Technologies announced a pathway for developers who want to use VRWorks to accellerate rendering for VR applications developed using the Unity Game Engine. VR applications require stereo rendering at 90 fps to give users a smooth experience and this requires a lot of performance. VRWorks unlocks GPU performance so developers can concentrate on making great content.

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Supercomputer Helps Understand How Jupiter Evolved

Research, Astronomy & Astrophysics, Cluster / Supercomputing, cu, Government / National Labs, Higher Education / Academia, Tesla

Nadeem Mohammad, posted Nov 02 2016

Researchers from ETH Zürich and the Universities of Zürich and Bern simulated different scenarios on the computing power of the GPU-accelerated Swiss National Supercomputing Centre (CSCS) to find out how young giant planets exactly form and evolve. “We pushed our simulations to the limits in terms of the complexity of the physics added to the

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AI-Powered Crib Cam Monitors Your Baby

News, Research, Cloud, DIGITS, Image Recognition, Internet / Communications, Internet of Things, Tesla

Nadeem Mohammad, posted Oct 31 2016

BabbyCam is a new deep learning baby monitor that recognizes your baby, monitors their emotions and will alert you if their face is covered. As a new parent himself, the developer of the camera was in search for a solution with the ability to identify if the infant was on its stomach, one of the

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Automated Analysis of Disaster Damage

Research, cuDNN, GeForce, Higher Education / Academia, Image Recognition

Nadeem Mohammad, posted Oct 28 2016

Researchers from Purdue University are using deep learning to dramatically reduce the time it takes for engineers to assess damage to buildings after disasters. Engineers need to quickly document the damage to buildings, bridges and pipelines after a disaster. “These teams of engineers take a lot of photos, perhaps 10,000 images per day, and these

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