IARPA Opens Machine Learning Challenge

The Intelligence Advanced Research Projects Activity (IARPA) recently opened registration for a prize challenge in automated analysis and classification of objects within satellite imagery. IARPA’s Functional Map of the World (fMoW) Challenge asks developers to build machine learning algorithms capable of classifying the function of facilities, specific buildings, and land—information used by intelligence personnel to support defense, humanitarian, and disaster response missions. “We are hoping to introduce learning opportunities for the geospatial and deep learning communities to integrate their approaches and increase the exposure to the scientific gains that could be made by combining these two disciplines,” said IARPA spokesperson Charles Carithers. Labeling objects within satellite imagery is time-consuming when handled by a human analyst and contributes to operator burnout. This challenge aims to produce breakthroughs in deep learning analysis that will accelerate this process and, in the absence of human error, improve accuracy. In July and August, IARPA will release in two batches one of the world’s largest publicly available satellite image data sets to date, including roughly one million image “chips.” Each chip will highlight an unidentified point of interest and the library will contain 62 pre-defined categories. This data is the fuel participants will feed their algorithms.…

Link to Full Article: IARPA Opens Machine Learning Challenge

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