Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
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High-dimensional spatial simulation ensemble analysis

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3429344 ◽

2020 ◽

Author(s):

Mai Dahshan ◽

Leanna House ◽

Nicholas Polys

Keyword(s):

High Dimensional ◽

Spatial Simulation ◽

Ensemble Analysis

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Giving meaning to unsupervised EO change detection rasters

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3429347 ◽

2020 ◽

Author(s):

Jordane Dorne ◽

Nathalie Aussenac-Gilles ◽

Catherine Comparot ◽

Cassia Trojahn ◽

Romain Hugues

Keyword(s):

Change Detection

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Comparative analysis of deep transfer learning performance on crop classification

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3431369 ◽

2020 ◽

Author(s):

Krishna Karthik Gadiraju ◽

Ranga Raju Vatsavai

Keyword(s):

Comparative Analysis ◽

Transfer Learning ◽

Learning Performance ◽

Crop Classification

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Creating cloud-free satellite imagery from image time series with deep learning

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3429345 ◽

2020 ◽

Author(s):

Stefan Oehmcke ◽

Tzu-Hsin Karen Chen ◽

Alexander V. Prishchepov ◽

Fabian Gieseke

Keyword(s):

Time Series ◽

Deep Learning ◽

Satellite Imagery

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A geographic computational visual feature database for natural and anthropogenic phenomena analysis from multi-resolution remote sensing imagery

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3429349 ◽

2020 ◽

Author(s):

Yulin Cao ◽

Butros M. Dahu ◽

Grant J. Scott

Keyword(s):

Remote Sensing ◽

Visual Feature ◽

Remote Sensing Imagery ◽

Feature Database

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Convolutional neural networks with hierarchical context transfer for high-resolution spatiotemporal predictions

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3429346 ◽

2020 ◽

Author(s):

Ksenia D. Mukhina ◽

Alexander A. Visheratin ◽

Denis Nasonov

Keyword(s):

Neural Networks ◽

High Resolution ◽

Convolutional Neural Networks ◽

Context Transfer

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Scalable unsupervised multi-criteria trajectory segmentation and driving preference mining

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data ◽

10.1145/3423336.3429348 ◽

2020 ◽

Author(s):

Florian Barth ◽

Stefan Funke ◽

Tobias Skovgaard Jepsen ◽

Claudius Proissl

Keyword(s):

Trajectory Segmentation

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Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial DataLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By ACM

High-dimensional spatial simulation ensemble analysis

Giving meaning to unsupervised EO change detection rasters

Comparative analysis of deep transfer learning performance on crop classification

Creating cloud-free satellite imagery from image time series with deep learning

A geographic computational visual feature database for natural and anthropogenic phenomena analysis from multi-resolution remote sensing imagery

Convolutional neural networks with hierarchical context transfer for high-resolution spatiotemporal predictions

Scalable unsupervised multi-criteria trajectory segmentation and driving preference mining

Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
Latest Publications