Crater-Counting AI Algorithm Discovers ~7,000 Moon Craters, Advances Extraterrestrial Mapping Techniques

Moon Crater Identification Project Led By Ari Silburt At Penn State University And Mohamad Ali-Dib At University Of Toronto Uses Algorithm To Find Craters >5-km Diameter, Leads To Discovery Of 6,883 New Craters In Only A Few Hours & Confirms Previously Known Craters With Very Few Errors; Lunar Craters Are Significant For Solar System Origin Clues, Establishing Areas Of Interest For Exploration, Science, Sample Return, Human Settlement; Artificial Intelligence Mapping Techniques For Big Data Could Be Used For Solar / Extrasolar Systems, Geologic / Other Observations
Credits: NASA, JPL, Caltech, Ari Silburt (L), Mohamad Ali-Dib (R), Univ. of Toronto, PSRD, David Trang, LROC WAC, et al






Lack Of Atmosphere & Global Magnetic Fields On Moon Reflect Some Solar Wind Back Into Space From Surface According To IRF Researcher Charles Lue; Measurements Taken By Chandrayaan-1 Sub-keV Atom Reflecting Analyzer (SARA) / Solar WInd Monitor (SWIM) Revealing Up To 10% Of Solar Wind Reflects Back Into Space; Lue States “This Knowledge Is Of Great Importance To The Lunar Space Environment” And Is Mapping Areas Where Solar Wind Is Most Prominent; Findings Could Be Utilized To Estimate How Much Water Is On Lunar Surface
In Year 7, LRO Continues To Provide Information Useful For Decades Of Future Human Exploration; LRO Deputy PI Benjamin Greenhagen Comments “We Honor The Moon As A Global Scientific Legacy”; Data Reveals 