Interactive Mars Image Content-Based Search with Interpretable Machine Learning

arXiv:2402.16860v1 Announce Type: new
Abstract: The NASA Planetary Data System (PDS) hosts millions of images of planets, moons, and other bodies collected throughout many missions. The ever-expanding nature of data and user engagement demands an interpretable content classification system to support scientific discovery and individual curiosity. In this paper, we leverage a prototype-based architecture to enable users to understand and validate the evidence used by a classifier trained on images from the Mars Science Laboratory (MSL) Curiosity rover mission. In …

abstract arxiv classification cs.cv cs.ir curiosity data discovery engagement image images interactive machine machine learning mars nasa nature paper scientific discovery search support type user engagement