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Semantic segmentation on aerial and satellite imagery
RoboSat is an end-to-end pipeline written in Python 3 for feature extraction from aerial and satellite imagery. Features can be anything visually distinguishable in the imagery for example: buildings, parking lots, roads, or cars.
...Of course you may specify JASP for advanced data editing and RapidMiner for advanced prediction modeling.
DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy.
This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.