To be effective in complex operations, the U.S. military requires understanding about populations in the physical and information environments. Operations executed without sufficient understanding lead to unintended consequences with potentially far-reaching implications. We present Apropos, a platform that aims to improve mission outcomes through socioculturally informed course of action analyses. Apropos uses deep learning over multiple data modalities to efficiently derive information on operational and civil factors. Research efforts focus on deep learning approaches and model fusion techniques centered around knowledge graph embeddings enabling semantic search, predictive surfaces, and other analytics (e.g. route planning and site selection).
Jake Popham, Micheal Forkin, Nicholas Hamblet, and Bryce Inouye, "Data fusion for sociocultural place understanding using deep learning," Proc. SPIE 10653, Next-Generation Analyst VI, 106530E (Presented at SPIE Defense + Security: April 16, 2018; Published: 27 April 2018); https://doi.org/10.1117/12.2306881.
Conference Presentations are recordings of oral presentations given at SPIE conferences and published as part of the proceedings. They include the speaker's narration with video of the slides and animations. Most include full-text papers. Interactive, searchable transcripts and closed captioning are now available for 2018 presentations, with transcripts for prior recordings added daily.
Search our growing collection of more than 16,000 conference presentations, including many plenaries and keynotes.