Geoweaver for Better Deep Learning: A Review of Cyberinfrastructure
The deep stack and tremendous amount of computational parameters in deep learning models greatly increases the challenges of pre-processing, training, testing, and post- processing geospatial datasets quickly and efficiently. This session will discuss the latest progresses on constructing advanced cyberinfrastructure for deep learning on satellite-based or field-observed geospatial datasets. The goal is to bring community experiences together and collaborate on building advanced geospatial cyberinfrastructure addressing the big questions raised in solving fundamental geoscience problems using deep learning models.
This presentation was given in July 2019 at the Earth Science Information Partners (ESIP) Summer Meeting held in Tacoma, Washington.
EarthCube Integration: CyberWay--Integrated Capabilities of EarthCube Building Blocks for Facilitating Cyber-based Innovative Way of Interdisciplinary Geoscience Studies
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