This workshop will bring geoscientists, computer scientists, engineers, entrepreneurs, and decision makers from academia, industry, and government to discuss the latest trends, successes, challenges, and opportunities in the field of deep learning for geographical data mining and knowledge discovery. Through the workshop, attendees can exchange the latest techniques and workflows used in deep learning for geographical and spatial research. This workshop has a combination of computational methods and geographic research, and fits the general theme of ACM SIGSPATIAL.
The workshop will provide an interactive forum to engage in discussions, shape the research directions, and disseminate state-of-the-art solutions. Examples of topics include but not limited to:
Novel deep neural network architectures and algorithms for geographic information analysis;
Deep learning for object extraction (such as roads, buildings) from remote sensing images;
Deep learning for geographic information extraction from text (e.g. social media, web documents, and news);
Deep learning models for multi/hyperspectral data analysis;
Deep learning methods for urban growth prediction;
AI and deep learning in autonomous transportation and high-precision maps;
Unsupervised learning
HPC architecture for deep learning
Applications of deep learning in disaster response.
11月07日
2017
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