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Discovery of 108 Faint Asteroid Candidates in Archival NEOWISE Infrared Space Telescope Images Using a Custom Deep Learning-Based Pipeline

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  • Gauri Vani Todur

Abstract

Near Earth asteroids (NEAs) are defined as minor planets with orbits close to Earth that could pose potential collision risks. Over 98% of the estimated 3 million small near-Earth asteroids (19-140 meters) remain undiscovered due to their faintness, leaving Earth vulnerable to impacts like the undetected 18-meter-sized 2013 Chelyabinsk meteor that caused injuries to ∼1600 people. The purpose of this research is to develop an automated deep learning-based pipeline to accurately discover small, faint, near-Earth asteroids. Because of its ability to pick up faint thermal signals, archival image data in the W2 band from the Near-Earth Object Wide-Field Infrared Survey Explorer (NEOWISE) was used. First, I filtered out stationary objects using a star masking process, and bright artifact pixel patterns by referencing WISE archival bitmask frames.

Suggested Citation

  • Gauri Vani Todur, 2026. "Discovery of 108 Faint Asteroid Candidates in Archival NEOWISE Infrared Space Telescope Images Using a Custom Deep Learning-Based Pipeline," International Journal of Innovative Science and Research Technology (IJISRT), IJISRT Publication, vol. 11(06), pages 3212-3225, July.
    • Handle: RePEc:cvr:ijisrt:2026:06:ijisrt26jun1572
    DOI: https://doi.org/10.38124/ijisrt/26jun1572
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