Automated Feature Identification in Machine Learning Trials

MINNETONKA, Minnesota, USA, 1 June 2017 – East View Geospatial (EVG), a provider of content-rich cartographic products, continues to enhance the accuracy of automated feature identification using its newly developed training data sets in supervised machine learning applications. The impressive early results pertained to automated recognition of building structures in an ongoing pilot project in Papua New Guinea (PNG).

“Our goal is to create a state-of-the-art process that produces the highest quality training data available for the users and developers of supervised machine learning technology,” said Rod Buhrsmith, EVG Business Development. “In just a few months, we have made significant progress and expect to push the accuracy even higher.”

EVG will be available to discuss the PNG pilot in private meetings next week at the 2017 GEOINT Symposium in San Antonio. Sample data sets are being offered at no charge.

“We continue to seek partners in the GIS and GEOINT ecosystems who are building geospatial machine learning capabilities and need high-quality source data to break through to the next level of big data analytics,” added Buhrsmith.

EVG initiated the PNG pilot early this year with multiple organizations actively engaged in enhancing and calibrating big data algorithms. Most supervised machine learning applications in geospatial currently entail either automated extraction of information from massive data sets or management and tracking of high-velocity, high-volume data streaming from numerous remote sensing platforms.

In its early phases, the pilot has concentrated on developing foundational training data sets tailored to identification of transportation, hydrology, infrastructure and land use/land cover in half-meter satellite imagery. EVG and its partners are now expanding their research to include imagery and streaming video from other sources, including aircraft, unmanned aerial systems (UAS), and terrestrial sensors.

“Our role in this space is to become the authoritative source of training data, either custom made or archived in a commercial library,” said Mark Knapp, EVG Product Development. “We have the data sourcing expertise and MilSpec production capabilities to accommodate any geospatial application.”