{"id":32594,"date":"2023-06-09T12:05:00","date_gmt":"2023-06-09T19:05:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=32594"},"modified":"2023-06-09T12:05:45","modified_gmt":"2023-06-09T19:05:45","slug":"usgif-releases-new-white-paper-the-evolving-role-of-synthetic-data-in-geoint-tradecraft","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2023\/06\/09\/usgif-releases-new-white-paper-the-evolving-role-of-synthetic-data-in-geoint-tradecraft\/","title":{"rendered":"USGIF Releases New White Paper: The Evolving Role of Synthetic Data in GEOINT Tradecraft\u00a0"},"content":{"rendered":"\n

Recent advancements in AI have created many opportunities in the GEOINT field, not only by improving imagery analysis techniques, but also by creating synthetic training data for AI algorithms to work more efficiently and accurately. Prior to the innovation of synthetic training data, human inputs would be needed for training AI algorithms. By integrating AI into producing pixel and non-pixel based synthetic data, the process of training and validating a model can be done quicker and cheaper. In addition to training models, synthetic data is used today for predicting how different camouflage patterns or other counter detection techniques will appear in the field. Synthetic data generation can also be used to test cutting edge sensors.  <\/p>\n\n\n\n

Download white paper: The Evolving Role of Synthetic Data in GEOINT Tradecraft<\/a> <\/p>\n\n\n\n

\n

\u201cSynthetic data is one of the keys to unlocking actionable intelligence from datasets that are growing far faster than humans can inspect and describe them,\u201d said USGIF Modeling, Simulation & Gaming Working Group (MS&G WG) Co-chair Chris Andrews, Chief Operating Officer, Rendered.ai. \u201cWhether extracting information from structured SIGINT and text or unstructured sensor-based imagery and video, synthetic data\u2014created through both generative and physics-based techniques\u2014enables us to rapidly engineer and validate algorithms to monitor and respond to continuously evolving conditions on the battlefield and in everyday activity.\u201d <\/p>\n<\/blockquote>\n\n\n\n

\n

\u201cWe live in a world where reality, augmented reality, virtual reality and all of the derivatives of each are becoming part of the mental landscape of both GEOINT professionals and consumers in the general population,\u201d said MS&G WG Co-chair Barry Tilton, Technology Evangelist, Office of the CTO, Maxar. \u201cThis paper is a welcome introduction to how artificial content can serve as a bridge\u2014allowing the testing of new ideas and as a training framework for generative AI. A great power of synthetic data is the ability to enhance the real\u2014allowing a look into the past and future.\u201d <\/p>\n<\/blockquote>\n\n\n\n

About the USGIF Modeling, Simulation & Gaming Working Group <\/strong><\/p>\n\n\n\n

The Modeling, Simulation & Gaming Working Group<\/a> (MS&G) educates and informs the global Geospatial-Intelligence (GEOINT) community on how modeling, simulation and gaming technology can be made more interoperable with GEOINT tradecraft.  We seek to collaborate with Industry, Academia, and Government to highlight advanced research concepts and commercial technology developments supporting geospatial modeling, simulation and gaming systems that are capable of delivering authoritative and relevant GEOINT at the point of need.  A core tenant of our collaboration strategy is to maintain close working relationships with both the Open Geospatial Consortium (OGC) Interoperability, Simulation and Gaming (IS&G) Working Group and the Simulation Interoperability Standards Organization (SISO). <\/p>\n\n\n\n

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Join us on Facebook: https:\/\/www.facebook.com\/insideBIGDATANOW<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Recent advancements in AI have created many opportunities in the GEOINT field, not only by improving imagery analysis techniques, but also by creating synthetic training data for AI algorithms to work more efficiently and accurately. Prior to the innovation of synthetic training data, human inputs would be needed for training AI algorithms.<\/p>\n","protected":false},"author":10513,"featured_media":32610,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[526,115,180,73,268,56,1,70],"tags":[437,592,1069,96],"acf":[],"yoast_head":"\nUSGIF Releases New White Paper: The Evolving Role of Synthetic Data in GEOINT Tradecraft\u00a0 - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2023\/06\/09\/usgif-releases-new-white-paper-the-evolving-role-of-synthetic-data-in-geoint-tradecraft\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"USGIF Releases New White Paper: The Evolving Role of Synthetic Data in GEOINT Tradecraft\u00a0 - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"Recent advancements in AI have created many opportunities in the GEOINT field, not only by improving imagery analysis techniques, but also by creating synthetic training data for AI algorithms to work more efficiently and accurately. 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As part of the investment, Appen has formed a commercial partnership agreement with Mindtech.","rel":"","context":"In "AI Deep Learning"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":32673,"url":"https:\/\/insidebigdata.com\/2023\/06\/17\/synthetic-data-the-cure-to-data-drift\/","url_meta":{"origin":32594,"position":2},"title":"Synthetic Data: The Cure to Data Drift?","date":"June 17, 2023","format":false,"excerpt":"In this contributed article, Steve Harris, CEO of\u00a0Mindtech, discusses how data drift is a growing problem affecting almost two-thirds of organizations. Synthetic training data is becoming richer, more diverse, and closely aligned to real world data and has emerged as a solution to overcome the potential of data drift.","rel":"","context":"In "AI Deep Learning"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2023\/06\/Synthetic_data_shutterstock_2306922019_special.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":28647,"url":"https:\/\/insidebigdata.com\/2022\/03\/07\/the-decade-of-synthetic-data-is-underway\/","url_meta":{"origin":32594,"position":3},"title":"The Decade of Synthetic Data is Underway","date":"March 7, 2022","format":false,"excerpt":"In this contributed article, Gil Elbaz, CTO and Co-founder of Datagen, sheds light on new developments that will make the \u201820s the decade when synthetic data finally breaks through to become a mainstream part of practical AI applications. Artificial intelligence algorithms are only as good as the data that train\u2026","rel":"","context":"In "AI Deep Learning"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":27623,"url":"https:\/\/insidebigdata.com\/2021\/11\/17\/book-review-synthetic-data-for-deep-learning\/","url_meta":{"origin":32594,"position":4},"title":"Book Review: Synthetic Data for Deep Learning","date":"November 17, 2021","format":false,"excerpt":"\"Synthetic Data for Deep Learning,\" by Sergey I. Nikolenko (published by Springer), represents a very good academic treatment of the subject. But what gives the book more street cred is the fact that the author is also Chief Research Officer for Synthesis AI, a start-up company pioneering this accelerating field.\u2026","rel":"","context":"In "AI Deep Learning"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/insidebigdata.com\/wp-content\/uploads\/2021\/11\/SyntheticData_book_fig1.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":29641,"url":"https:\/\/insidebigdata.com\/2022\/06\/22\/making-a-case-for-the-first-open-source-platform-for-synthetic-data\/","url_meta":{"origin":32594,"position":5},"title":"Making a Case for the First Open Source Platform for Synthetic Data","date":"June 22, 2022","format":false,"excerpt":"In this special guest feature, Yashar Behzadi, Ph.D., CEO and Founder of Synthesis AI, discusses on the importance of a community like OpenSynthetics in developing more capable AI models. 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