Labelmars.det: Crowd-sourcing an extremely large high quality Martian image dataset.

Wallace, I.; Schwenzer, S. P.; Woods, M.; Read, N.; Wright, S.; Waumsley, K. and Joudrier, L. (2017). Labelmars.det: Crowd-sourcing an extremely large high quality Martian image dataset. In: 48th Lunar and Planetary Science Conference, 20-24 Mar 2017, Houston.

URL: http://www.hou.usra.edu/meetings/lpsc2017/pdf/1170...

Abstract

The observation of landforms, outcrops and small features within a (Martian) landscape is key to the understanding of its geologic past as well as present environmental conditions. Studies of such features have – for example – revealed the nature of streambeds at Gale Crater, and allowed to study Aeolian bedforms as they were encountered by the Curiosity, and Spirit rovers. With two active rovers (Opportunity, Curiosity) currently on Mars, and two more to be launched in 2020 (ExoMars, Mars2020), the imaging data sets are a huge, growing resource, which need to be explored as best as possible.

LabelMars (www.labelmars.net) is a citizen science activity to collect geological annotations of Martian rover navigation camera images. As part of the ESA NOAH (Novelty Or Anomaly Hunter) project it will provide a large, high quality dataset to develop stateof-the-art machine vision algorithms for autonomous science detection, targeted at future rover missions.

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