Here one can find the installation, metadata and some manuals on how to use the FineET modules, either stand-alone or together.
Coming soon, stay tuned!
- Downloading open-source FineET project
- Installing the software
- Running the models locally
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 Kevin Bruhwiler*, Paahuni Khandelwal, Daniel Rammer*, Samuel Armstrong*, Sangmi Lee Pallickara, and Shrideep Pallickara. Lightweight, Embeddings Based Storage and Model Construction Over Satellite Data Collections. Proceedings of the IEEE International Conference on Big Data (IEEE BigData). Atlanta, USA. 2020.
 Paahuni Khandelwal, Daniel Rammer, Shrideep Pallickara, and Sangmi Lee Pallickara. Mind the Gap: Generating Imputations for Satellite Data Collections at Myriad Spatiotemporal Scopes. (To appear) Proceedings of the 21st IEEE/ACM international Symposium on Cluster, Cloud and Internet Computing (CCGrid). 2021. Melbourne, Australia.
 Rammer, Daniel, Kevin Bruhwiler, Paahuni Khandelwal, Samuel Armstrong, Shrideep Pallickara, and Sangmi Lee Pallickara. “Small is Beautiful: Distributed Orchestration of Spatial Deep Learning Workloads.” In 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), pp. 101-111. IEEE Computer Society, 2020.
 Rammer, Daniel, Sangmi Lee Pallickara, and Shrideep Pallickara. “Towards Timely, Resource-Efficient Analyses Through Spatially-Aware Constructs within Spark.” In 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), pp. 46-56. IEEE, 2020.
 Bruhwiler, Kevin, Thilina Buddhika, Shrideep Pallickara, and Sangmi Lee Pallickara. “Iris: Amortized, Resource Efficient Visualizations of Voluminous Spatiotemporal Datasets.” In 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), pp. 47-56. IEEE, 2020.