Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images

التفاصيل البيبلوغرافية
العنوان: Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images
المؤلفون: Andresini G., Appice A., Dell'Olio D., Malerba D.
المساهمون: Bandini, S., Gasparini, F., Mascardi, V., Palmonari, M., Vizzari, G., Andresini, G., Appice, A., Dell'Olio, D., Malerba, D.
بيانات النشر: Springer Science and Business Media Deutschland GmbH
GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
سنة النشر: 2022
المجموعة: Università degli Studi di Bari Aldo Moro: CINECA IRIS
مصطلحات موضوعية: Change detection, Earth observation, Sentinel-2 image, Siamese network, Transfer learning
الوصف: The Earth’s surface is constantly changing due to various anthropogenic and natural causes. Leveraging machine learning to monitor land cover changes over time may provide valuable information on the transformation of the Earth’s environment. This study focuses on the discovery of land cover changes in bi-temporal, Sentinel-2 images. In particular, we rely on a Siamese network trained with labelled, imagery data of the same Earth’s scene acquired with Sentinel-2 at different times. Subsequently, we adopt a transfer learning strategy to adapt the Siamese network to Sentinel-2 data acquired in any new unlabeled scene. To deal with the lack of change labels in the new scene, transfer learning is performed with change pseudo-labels estimated in the new scene in unsupervised manner. We assess the effectiveness of the proposed change detection method in two couples of images acquired with Sentinel-2, at different times, in the urban areas of Cupertino and Las Vegas.
نوع الوثيقة: conference object
اللغة: English
العلاقة: info:eu-repo/semantics/altIdentifier/isbn/978-3-031-08420-1; info:eu-repo/semantics/altIdentifier/isbn/978-3-031-08421-8; info:eu-repo/semantics/altIdentifier/wos/WOS:000876859300033; ispartofbook:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 20th International Conference of the Italian Association for Artificial Intelligence, AIxIA 2021; volume:13196; firstpage:478; lastpage:489; numberofpages:12; serie:LECTURE NOTES IN COMPUTER SCIENCE; https://hdl.handle.net/11586/417131Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85135017874
DOI: 10.1007/978-3-031-08421-8_33
الإتاحة: https://doi.org/10.1007/978-3-031-08421-8_33Test
https://hdl.handle.net/11586/417131Test
رقم الانضمام: edsbas.E8ECCF3F
قاعدة البيانات: BASE