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ORCID9th BigSpatial@SIGSPATIAL 2020: Seattle, WA, USA
- Varun Chandola, Ranga Raju Vatsavai, Ashwin Shashidharan:
BIGSPATIAL '20: Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial@SIGSPATIAL 2020, Seattle, WA, USA, November 3, 2020. ACM 2020, ISBN 978-1-4503-8162-8 - Krishna Karthik Gadiraju, Ranga Raju Vatsavai:
Comparative analysis of deep transfer learning performance on crop classification. 1:1-1:8 - Mai Dahshan, Leanna House, Nicholas F. Polys
:
High-dimensional spatial simulation ensemble analysis. 2:1-2:4 - Stefan Oehmcke, Tzu-Hsin Karen Chen, Alexander V. Prishchepov, Fabian Gieseke:
Creating cloud-free satellite imagery from image time series with deep learning. 3:1-3:10 - Ksenia D. Mukhina, Alexander A. Visheratin, Denis A. Nasonov:
Convolutional neural networks with hierarchical context transfer for high-resolution spatiotemporal predictions. 4:1-4:10 - Jordane Dorne, Nathalie Aussenac-Gilles, Catherine Comparot, Cássia Trojahn, Romain Hugues:
Giving meaning to unsupervised EO change detection rasters: a semantic-driven approach. 5:1-5:10 - Florian Barth, Stefan Funke, Tobias Skovgaard Jepsen, Claudius Proissl:
Scalable unsupervised multi-criteria trajectory segmentation and driving preference mining. 6:1-6:10 - Yulin Cao, Butros M. Dahu, Grant J. Scott:
A geographic computational visual feature database for natural and anthropogenic phenomena analysis from multi-resolution remote sensing imagery. 7:1-7:10
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