Join us in advancing scientific discovery by helping train an AI system to detect anomalies in visual data from our cameras.

By categorizing images, you’ll help us identify common patterns, filter out known phenomena, and sharpen our ability to detect the unusual. This work supports the development of a machine learning model that will improve the accuracy of our anomaly detection - and make our evidence archive far more usable and insightful.

This project is ideal for anyone who enjoys visual analysis, detail-oriented work, or simply wants to contribute to scientific research. No technical background is needed - just curiosity, patience, and a good sense of observation.

Your role will be to help us distinguish between familiar light sources and environmental elements - such as car headlights, motion-triggered lights, lightning, auroras, meteors, satellites, and space debris - as well as daylight objects like birds, insects, leaves, floating seeds, and even lens flares, rain, frost, or spider webs on the camera lens.

The more accurately we identify the known, the better we can study the unknown. With your help, we can move one step closer to understanding the phenomenon known as the Hessdalen Lights.