Publication profile
Publication profile
Olav Brautaset
Name:
Olav Brautaset
Title:
Seniorforsker / Senior Research Scientist
Phone:
(+47) +47 22 85 26 31 Mob: +47 480 75 679
Email:
obr [at] nr [dot] no
Scientific areas:
Machine learning, Deep learning, Image analysis
Add to contacts (vCard) Show publications
Academic article
2022
. Evaluation of echosounder data preparation strategies for modern machine learning models. Fisheries Research (ISSN 0165-7836). 254 doi: 10.1016/j.fishres.2022.106411. 2022. Arkiv
2021
. Semi-supervised target classification in multi-frequency echosounder data. ICES Journal of Marine Science (ISSN 1054-3139). 78(7) pp 2615-2627. doi: 10.1093/icesjms/fsab140. 2021. Arkiv Fulltekst
2020
. A mammography classification model trained from image labels only. Proceedings of the Northern Lights Deep Learning Workshop. doi: 10.7557/18.6244. 2020.
. 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. Arkiv
2016
. Activity-based risk analysis for process plant operations. Institution of Chemical Engineers Symposium Series (ISSN 0307-0492). 2016-January(161) 2016. Arkiv
Academic chapter/article/Conference paper
2015
. Risk information for operational decision making in oil and gas operations. In: Safety and Reliability of Complex Engineered Systems. (ISBN 9781138028791). pp 405-413. doi: 10.1201/b19094-57. 2015. Arkiv
Academic lecture
2021
. Marine Acoustic Classification: Supervised Semantic Segmentation of Echosounder Data using CNNs. Visual Intelligence Seminar series; Online, 2/18/2021.
2019
. Automatic fish identification from multi-frequency acoustic data using deep learning. ICES Annual Science Conference 2019, 9/9/2019.
. Applying deep learning to non-standard image data - a case study on marine acoustics. Northern Lights Deep Learning Workshop 2019; Tromsø, 1/9/2019 - 1/10/2019.
. Automated acoustic data processing with deep learning. Norway-US Workshop on Machine Learning to Improve Science for the Sustainability of Living Ocean Resources; Bergen, 5/23/2019 - 5/25/2019.
2016
. Quantitative risk analysis for decision support in process plant operations. 12th Global Congress on Process Safety; Houston, 4/10/2016 - 4/13/2016.
2015
. Risk information for operational decision making in oil and gas operations. ESREL 2015; Zurich, 9/7/2015 - 9/10/2015.
Lecture
2020
. Automatic target classification using supervised learning on marine acoustic data with auxiliary information. Classifying fisheries acoustic data, 11/9/2020.
2019
. Automated acoustic data processing with deep learning. AI lounge; Oslo, 5/28/2019.
Poster
2022
. A mammography classification model trained from image labels only. NLDL 2022; Online, 1/10/2022.
2021
. Improving marine acoustic target classification with context information. Visual Intelligence Days 2021; Oslo, 10/19/2021 - 10/20/2021.
Report
2022
. Procedures for mammographic screening with machine learning. Norsk Regnesentral. NR-notat SAMBA/17/22. pp 16. 2022.
. Machine learning for screening mammography. Norsk Regnesentral. NR-notat SAMBA/18/22. pp 33. 2022.
2021
. Fisheries acoustics and Acoustic Target Classification - Report from the COGMAR/CRIMAC workshop on machine learning methods in fisheries acoustics. Havforskningsinstituttet. Rapport fra havforskningen 2021 - 25. pp 25. 2021. Fulltekst Arkiv
. Machine learning for screening mammography. Norsk Regnesentral. NR-notat SAMBA/05/21. pp 52. 2021.
2020
. Feasibility study: Non-verbal communication interpreter - Image-based methodological approaches. norsk regnesentral. NR-notat SAMBA/03/20. pp 49. 2020.
. Machine learning for screening mammography - Initial analyses on a first limited dataset. Norsk Regnesentral. NR-notat SAMBA/16/20. pp 45. 2020.
| Name: | Olav Brautaset |
| Title: | Seniorforsker / Senior Research Scientist |
| Phone: | (+47) +47 22 85 26 31 Mob: +47 480 75 679 |
| Email: | obr [at] nr [dot] no |
| Scientific areas: | Machine learning, Deep learning, Image analysis |
| Add to contacts (vCard) |
| Show publications |
Academic article
2022
. Evaluation of echosounder data preparation strategies for modern machine learning models. Fisheries Research (ISSN 0165-7836). 254 doi: 10.1016/j.fishres.2022.106411. 2022. Arkiv
2021
. Semi-supervised target classification in multi-frequency echosounder data. ICES Journal of Marine Science (ISSN 1054-3139). 78(7) pp 2615-2627. doi: 10.1093/icesjms/fsab140. 2021. Arkiv Fulltekst
2020
. A mammography classification model trained from image labels only. Proceedings of the Northern Lights Deep Learning Workshop. doi: 10.7557/18.6244. 2020.
. 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. Arkiv
2016
. Activity-based risk analysis for process plant operations. Institution of Chemical Engineers Symposium Series (ISSN 0307-0492). 2016-January(161) 2016. Arkiv
Academic chapter/article/Conference paper
2015
. Risk information for operational decision making in oil and gas operations. In: Safety and Reliability of Complex Engineered Systems. (ISBN 9781138028791). pp 405-413. doi: 10.1201/b19094-57. 2015. Arkiv
Academic lecture
2021
. Marine Acoustic Classification: Supervised Semantic Segmentation of Echosounder Data using CNNs. Visual Intelligence Seminar series; Online, 2/18/2021.
2019
. Automatic fish identification from multi-frequency acoustic data using deep learning. ICES Annual Science Conference 2019, 9/9/2019.
. Applying deep learning to non-standard image data - a case study on marine acoustics. Northern Lights Deep Learning Workshop 2019; Tromsø, 1/9/2019 - 1/10/2019.
. Automated acoustic data processing with deep learning. Norway-US Workshop on Machine Learning to Improve Science for the Sustainability of Living Ocean Resources; Bergen, 5/23/2019 - 5/25/2019.
2016
. Quantitative risk analysis for decision support in process plant operations. 12th Global Congress on Process Safety; Houston, 4/10/2016 - 4/13/2016.
2015
. Risk information for operational decision making in oil and gas operations. ESREL 2015; Zurich, 9/7/2015 - 9/10/2015.
Lecture
2020
. Automatic target classification using supervised learning on marine acoustic data with auxiliary information. Classifying fisheries acoustic data, 11/9/2020.
2019
. Automated acoustic data processing with deep learning. AI lounge; Oslo, 5/28/2019.
Poster
2022
. A mammography classification model trained from image labels only. NLDL 2022; Online, 1/10/2022.
2021
. Improving marine acoustic target classification with context information. Visual Intelligence Days 2021; Oslo, 10/19/2021 - 10/20/2021.
Report
2022
. Procedures for mammographic screening with machine learning. Norsk Regnesentral. NR-notat SAMBA/17/22. pp 16. 2022.
. Machine learning for screening mammography. Norsk Regnesentral. NR-notat SAMBA/18/22. pp 33. 2022.
2021
. Fisheries acoustics and Acoustic Target Classification - Report from the COGMAR/CRIMAC workshop on machine learning methods in fisheries acoustics. Havforskningsinstituttet. Rapport fra havforskningen 2021 - 25. pp 25. 2021. Fulltekst Arkiv
. Machine learning for screening mammography. Norsk Regnesentral. NR-notat SAMBA/05/21. pp 52. 2021.
2020
. Feasibility study: Non-verbal communication interpreter - Image-based methodological approaches. norsk regnesentral. NR-notat SAMBA/03/20. pp 49. 2020.
. Machine learning for screening mammography - Initial analyses on a first limited dataset. Norsk Regnesentral. NR-notat SAMBA/16/20. pp 45. 2020.
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