Using artificial intelligence planning to automate science data analysis for large image databases
Steve Chien, Forest Fisher, Helen Mortensen, Edisanter Lo, Ronald Greeley · 1997
This paper describes the use of AI planning tech-niques to represent scientific, image processing, and software tool knowledge to automate knowl-edge discovery and data mining (e.g., science data analysis) of large image databases. In particular, we describe two fielded systems. TheMultimission VICAR Planner (MVP) which has been deployed for 2 years and is currently supporting science prod-uct generation for the Galileo mission. MVP has..^rl..“^A G-n l ^ fll ^A..b.:..-l.T”“^ ” ^C,,,..^“h ” c-n-‘GUULGU lullrj LV 1111 I;Ulillll Ui lDSGB “I Hxpwrs ll”lll 4 hours to 15 minutes. The Automated SAR Im-age Processing system (ASIP) which is currently in use by the Dept. of Geology at ASU support-ing aeolian science analysis of synthetic aperture radar images. ASIP reduces the number of manual inputs in science product generation by lo-fold.