Computer searches telescope data for evidence of distant planets
As part of an effort to identify distant planets hospitable to life, NASA has established a crowdsourcing project in which volunteers search telescopic images for evidence of debris disks around stars, which are good indicators of exoplanets.
Using the results of that project, researchers at MIT have now trained a machine-learning system to search for debris disks itself. The scale of the search demands automation: There are nearly 750 million possible light sources in the data accumulated through NASA's Wide-Field Infrared Survey Explorer (WISE) mission alone.
In tests, the machine-learning system agreed with human identifications of debris disks 97 percent of the time. The researchers also trained their system to rate debris disks according to their likelihood of containing detectable exoplanets. In a paper describing the new work in the journal Astronomy and Computing, the MIT researchers report that their system identified 367 previously unexamined celestial objects as particularly promising candidates for further study.
Computer-aided discovery of debris disk candidates: A case study using the Wide-Field Infrared Survey Explorer (WISE) catalog (DOI: 10.1016/j.ascom.2018.02.004) (DX)
(Score: 0) by Anonymous Coward on Thursday April 05 2018, @07:21AM
for now, it's too expensive to use AI and robots to clean the litter on the streets.
(Score: 2) by Dr Spin on Thursday April 05 2018, @07:30AM
How about searching for SD card debris amongst the stars?
(Hard disks are unlikely to survive well in outer space).
Warning: Opening your mouth may invalidate your brain!