Ensemble Learning for Semantic Segmentation of Ancient Maya Architectures

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Deep learning methods hold great promise for the automatic analysis of large-scale remote sensing data in archaeological research. Here, we present a robust approach to locating ancient Maya architectures (buildings, aguadas, and platforms) based on integrated segmentation of satellite imagery and aerial laser scanning data. Deep learning models with different architectures and loss functions were trained and combined to form an ensemble for pixel-wise classification. We applied both training data augmentation as well as test-time augmentation and performed morphological cleaning in the postprocessing phase. Our approach was evaluated in the context of the “Discover the mysteries of the Maya: An Integrated Image Segmentation Challenge” at ECML PKDD 2021 and achieved one of the best results with an average IoU of 0.8183.
OriginalsprogEngelsk
TitelDiscover the Mysteries of the Maya : Selected Contributions from the Machine Learning Challenge & the Discovery Challenge Workshop, ECML PKDD 2021
RedaktørerDragi Kocev, Nikola Simidjievski, Ana Kostovska, Ivica Dimitrovski, Žiga Kokalj
Antal sider7
Udgivelsessted Ljubljana
ForlagJožef Stefan Institute
Publikationsdato2022
Sider13-19
Kapitel3
ISBN (Elektronisk)978-961-264-228-0
DOI
StatusUdgivet - 2022
Begivenhed European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2021 - Online, Bilbao, Spanien
Varighed: 13 sep. 202117 sep. 2021
https://2021.ecmlpkdd.org/index.html

Konference

Konference European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2021
LokationOnline
LandSpanien
ByBilbao
Periode13/09/202117/09/2021
Internetadresse

ID: 338603064