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Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

surface temperature Earth & Environmental Sciences
inertia Earth & Environmental Sciences
land surface Earth & Environmental Sciences
MODIS Earth & Environmental Sciences
remote sensing Earth & Environmental Sciences
ASCAT Earth & Environmental Sciences
thermography Agriculture & Biology
product development Earth & Environmental Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2010 2019

  • 8 Article
  • 3 Conference contribution
  • 1 Paper

Keras Spatial Extending deep learning frameworks for preprocessing and on-the-fly augmentation of geospatial data

Soliman, A. & Terstriep, J., Nov 5 2019, Proceedings of the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2019. Gao, S., Newsam, S., Zhao, L., Lunga, D., Hu, Y., Martins, B., Zhou, X. & Chen, F. (eds.). Association for Computing Machinery, Inc, p. 69-76 8 p. (Proceedings of the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, GeoAI 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
Remote sensing
Data handling
Computer vision
Derivatives
Deep learning
twitter
Regional planning
Urban planning
interaction
Gravitation

Social sensing of urban land use based on analysis of Twitter users' mobility patterns

Soliman, A., Soltani, K., Yin, J., Padmanabhan, A. & Wang, S., Jan 1 2017, In : PloS one. 12, 7, p. e0181657

Research output: Contribution to journalArticle

Land use
land use
Social Media
Information Storage and Retrieval
Lenses

UrbanFlow: Large-scale framework to integrate social media and authoritative landuse maps

Soltani, K., Soliman, A., Padmanabhan, A. & Wang, S., Jul 17 2016, Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale. Association for Computing Machinery, a2. (ACM International Conference Proceeding Series; vol. 17-21-July-2016).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Uncertainty
Big data

Datasets

Dataset for: Quantifying the geographic distribution of building coverage across the US for urban sustainability studies

Soliman, A. S. (Creator), Mackay, A. (Creator), Schmidt, A. R. (Creator), Allan, B. F. (Creator), Wang, S. (Creator), University of Illinois at Urbana-Champaign, Jun 5 2018

Dataset