Using Artificial Intelligence Planning to Automate Science Data Analysis for Large Image Databases

Steve Chien, Forest Fisher, Helen Mortensen, Edisanter Lo, Ronald Greeley

This paper describes the use of AI planning techniques to represent scientific, image processing, and software tool knowledge to automate knowledge discovery and data mining (e.g., science data analysis) of large image databases. In particular, we describe two fielded systems. The Multimission VICAR Planner (MVP) which has been deployed for 2 years and is currently supporting science product generation for the Galileo mission. MVP has reduced time to fill certain classes of requests from 4 hours to 15 minutes. The Automated SAR Image Processing system (ASIP) which is currently in use by the Dept. of Geology at ASU supporting aeolian science analysis of synthetic aperture radar images. ASIP reduces the number of manual inputs in science product generation by 10-fold.

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