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2017 GTC San Jose

S7124 - Drone Net: Using Tegra for Multi-Spectral Detection and Tracking in Shared Air Space

Session Speakers
Session Description

The challenge and opportunity presented by use of UAS "drones" in the national airspace has historic significance. The FAA estimates that by 2020 the drone market will be $98 billion with 7 million drones added annually. How drones ranging from professional service to hobby will safely share airspace is unclear. Preliminary research at Embry Riddle to develop a drone detector, which can be placed on rooftops and networked with other detectors and information services, has shown that multi-spectral electro-optical/infrared detection is quite effective. Our team is using NVIDIA Jetson systems in an EO/IR detector system. The NVIDIA Kepler architecture-based NVIDIA Tegra co-processor provides real-time object detection for aircraft and drones using salient object detection algorithms accelerated by GPUs. We'll present the power efficiency and real-time processing advantages GP-GPU provides compared to FPGA and multi-core, which we've also tested for this application.


Additional Session Information
Intermediate
Talk
Computer Vision and Machine Vision Deep Learning and AI Federal Intelligent Machines and IoT Video and Image Processing
25 minutes
Session Schedule