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GTC ON-DEMAND

Computer Vision
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Accelerated Functional Mapping of World with NVIDIA GPUs and Deep Learning
Abstract:
The functional mapping of man-made facilities from high-resolution remote sensing images provides timely high-fidelity land-use information and population distribution estimates, which facilitates federal, non-governmental agency and industrial expansion efficiency. We'll share our journey to deliver functional maps of the world that include building extraction, human settlement maps, mobile home parks, and facility mapping using a variety of remote sensing imagery. Our research addresses three frontier challenges; 1) distinct characteristics of remote sensing data for deep learning (including the model distribution shifts encountered with remote sensing images), multisensor sources, and data multi modalities; 2) training very large deep-learning models using multi-GPU and multi-node HPC platforms; 3) large-scale inference using ORNL's Titan and Summit with NVIDIA TensorRT. We'll also talk about developing workflows to minimize I/O inefficiency, doing parallel gradient-descent learning, and managing remote sensing data in HPC environment.
 
Topics:
Computer Vision, GIS, HPC and AI
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8420
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