Volunteer Develops Machine-Learning Tool to Identify Rare Clouds
Certain kinds of clouds are misbehaving – appearing more often and lower in the sky than they used to. To help identify the factors influencing these changes, scientists have asked people around the world with cameras to submit fresh images of these clouds as a part of the NASA-supported Space Cloud Watch project. The post Volunteer Develops Machine-Learning Tool to Identify Rare Clouds appeared…
Certain types of clouds, known as noctilucent or night-shining clouds (NLCs), are displaying unusual behavior by appearing more frequently and at lower altitudes than before. To aid in the identification of these mysterious clouds, NASA's Space Cloud Watch project has enlisted the help of volunteers worldwide to submit photos. Namai Chandra, a volunteer and creator of the Noctilucent Cloud Detector tool, recognized that the manual verification of NLC images by project leaders was both redundant and time-consuming.
In response, Namai developed a machine learning pipeline that can efficiently screen images, automatically classifying them as either NLCs or lower-altitude look-alikes. This pipeline combines image pre-screening, cloud classification, and confidence-based review routing, ensuring that human judgment is still crucial for the images that truly matter.
Drs. Chihoko Cullens and Brentha Thurairajah enthusiastically supported Namai's initiative, and the NLC identification tool is now being utilized by both project scientists and volunteers. As a result, those unsure about their NLC observations can now confidently share their photos, thanks to Namai's innovative tool.
Written by urgent.news from NASA Science's reporting — not their text. Machine-written — it may contain errors, so check the original before relying on it.
