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Publication profile

Publication profile

Anders Ueland Waldeland

Anders Ueland, Waldeland
Name: Anders Ueland Waldeland
Title: Forsker / Research Scientist
Phone: (+47) 98831007 Mob: 98831007
Email: andersuw [at] nr [dot] no
Scientific areas: Deep learning, Image analysis, Signal processing, Earth observation
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    Academic journal articles

    2020

    Brautaset, Olav; Waldeland, Anders Ueland; Johnsen, Espen; Malde, Ketil; Eikvil, Line; Salberg, Arnt-Børre; Handegard, Nils Olav. Acoustic classification in multifrequency echosounder data using deep convolutional neural networks. ICES Journal of Marine Science (ISSN 1054-3139). 77(4) pp 1391-1400. doi: 10.1093/icesjms/fsz235. 2020.

    Zhao, Hao; Waldeland, Anders U.; Serrano, Dany Rueda; Tygel, Martin; Iversen, Einar. Time-migration velocity estimation using Fréchet derivatives based on nonlinear kinematic migration/demigration solvers. Studia Geophysica et Geodaetica (ISSN 0039-3169). 64(1) pp 26-75. doi: 10.1007/s11200-019-1172-0. 2020.

    2019

    Waldeland, Anders U.; Coimbra, T.A.; Faccipieri, J. H.; Solberg, Anne H Schistad; Gelius, Leiv-J.. Fast estimation of prestack Common Reflection Surface parameters. Geophysical Prospecting (ISSN 0016-8025). 67(5) pp 1163-1183. doi: 10.1111/1365-2478.12740. 2019.

    2018

    Trier, Øivind Due; Cowley, David C.; Waldeland, Anders U.. Using deep neural networks on airborne laser scanning data: results from a case study of semi-automatic mapping of archaeological topography on Arran, Scotland. Archaeological Prospection (ISSN 1075-2196). 26(2) pp 165-175. doi: 10.1002/arp.1731. 2018. Full-text 

    Waldeland, Anders Ueland; Jensen, Are Charles; Gelius, Leiv-J.; Solberg, Anne H Schistad. Convolutional neural networks for automated seismic interpretation. The Leading Edge (ISSN 1070-485X). 37(7) pp 529-537. doi: 10.1190/tle37070529.1. 2018.

    Waldeland, Anders Ueland; Zhao, Hao; Faccipieri, J. H.; Solberg, Anne H Schistad; Gelius, Leiv-J.. Fast and robust common-reflection-surface parameter estimation. Geophysics (ISSN 0016-8033). 83(1) pp O1. doi: 10.1190/GEO2017-0113.1. 2018. Institutional archive 

    Abstracts at scientific conferences

    2018

    Zhao, Hao; Waldeland, Anders U.; Serrano, D. Rueda; Tygel, Martin; Iversen, Einar. Time-migration Tomography based on Reflection Slopes in Pre-stack Time-migrated Seismic Data. EAGE extended abstracts. . doi: 10.3997/2214-4609.201801383. 2018.

    Academic lectures

    2018

    Trier, Øivind Due; Waldeland, Anders Ueland; Cowley, David C.. Semi-automatic mapping of cultural heritage in Arran, Scotland, using deep neural networks on airborne laser scanning data. Konferanse, 46th Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2018); Tübingen, 20.03.2018 - 22.03.2018.

    Waldeland, Anders U.; Salberg, Arnt Børre; Marin, Alessandro. AI4EO Challenges in the context of the Great Green Wall Initiative. Konferanse, The ESA Earth Observation Phi-week; ESRIN, Roma, 12.11.2018 - 16.11.2018.

    Zhao, Hao; Waldeland, Anders U.; Rueda Serrano, Dany; Tygel, Martin; Iversen, Einar. Time-migration Tomography based on Reflection Slopes in Pre-stack Time-migrated Seismic. Konferanse, EAGE 80th Conference & Exhibition; Copenhagen, 11.06.2018 - 14.06.2018.

    2017

    Waldeland, Anders Ueland; Solberg, Anne H Schistad. Salt Classification Using Deep Learning. Konferanse, 79th EAGE Conference and Exhibition 2017; Paris, 11.06.2017 - 14.06.2017.

    Zhao, Hao; Waldeland, Anders Ueland; Serrano, Dany Rueda; Tygel, Martin; Iversen, Einar. Time-migration tomography based on reflection slopes, a first test. Seminar, Lofoten-seminaret i petroleumsgeofysikk; Svolvær, 15.08.2017 - 18.08.2017.

    2016

    Waldeland, Anders Ueland; Solberg, Anne H Schistad. 3D Attributes and Classification of Salt Bodies on Unlabelled Datasets. Konferanse, 78th EAGE Conference and Exhibition 2016; Wien, 30.05.2016 - 02.06.2016.

    Scientific lectures

    2018

    Waldeland, Anders U.. Seismic interpretation with deep learning. Annet, EAGE E-Lecture; https://www.youtube.com/watch?v=lm85Ap4OstM, 25.09.2018.

    Posters at scientific conferences

    2019

    Salberg, Arnt Børre; Waldeland, Anders U.. Deep learning based value chain for Sentinel-2 land cover mapping. ESA Living Planet Symphosium, 13.05.2019 - 17.05.2019.

    2018

    Waldeland, Anders U.; Reksten, Jarle Hamar; Salberg, Arnt Børre. Avalanche detection in sar images using deep learning. International Geoscience and Remote Sensing Symposium, IGARSS 2018; Valencia, 22.07.2018 - 27.07.2018.

    Doctoral dissertations

    2018

    Waldeland, Anders U.. Seismic image analysis for applications related to iterative 3D velocity model building. : Unipub UiO . pp 128. 2018.

    Reports

    2019

    Eikvil, Line; Waldeland, Anders U.; Holden, Marit; Salberg, Arnt Børre; Hauge, Ragnar; Barker, Daniel Martin L. Deep learning in seismic interpretation. Norsk Regnesentral, . NR-notat SAMBA/49/19. pp 39. 2019.

    2018

    Salberg, Arnt Børre; Waldeland, Anders U.. A New Value Chain for Earth Observation. Research agenda for AI and ML and the role of ESA. Norsk Regnesentral, . NR-notat SAMBA/35/18. pp 21. 2018.

    Salberg, Arnt Børre; Waldeland, Anders U.; Trier, Øivind Due. Next Generation Value Chain for Earth Observation (NGVEO). Final report. Norsk Regnesentral, . NR-notat SAMBA/37/18. pp 25. 2018.

    Trier, Øivind Due; Waldeland, Anders U.; Cowley, David C.. Automating archaeological object detection. Proof of concept – Arran survey. Norsk Regnesentral, Oslo. NR-notat SAMBA/08/18. pp 34. 2018. Full-text 

    Waldeland, Anders U.; Salberg, Arnt Børre; Trier, Øivind Due. Next Generation Value Chain for Earth Observation. Technical note: methodologies. Norsk Regnesentral, . NR-notat SAMBA/36/18. pp 41. 2018.

    Popular scientific lectures

    2019

    Waldeland, Anders U.. An Introduction to Machine Learning. FORCE Hackathon and symposium: Applied Machine Learning and Advanced Analytics with Oil and Gas Data; NDP, Stavanger, 20.09.2019.

    2018

    Waldeland, Anders U.. From Traditional Machine Learning to Deep Learning. FORCE Hackathon and Advances of Machine Learning on Subsurface Data; NDP, Stavanger, 18.09.2018.

Postal address:
Norsk Regnesentral/
Norwegian Computing Center
P.O. Box 114 Blindern
NO-0314 Oslo
Norway
Visit address:
Norsk Regnesentral
Gaustadalleen 23a
Kristen Nygaards hus
NO-0373 Oslo.
Phone:
(+47) 22 85 25 00
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Postal address: Norsk Regnesentral/Norwegian Computing Center, P.O. Box 114 Blindern, NO-0314 Oslo, Norway
Visit address: Norsk Regnesentral, Gaustadalleen 23a, Kristen Nygaards hus, NO-0373 Oslo.
Phone: (+47) 22 85 25 00
AddressHow to get to NR