Olav Brautaset

Fredrik Andreas Dahl; Olav Brautaset; Marit Holden; Line Eikvil; Marthe Larsen; et al. A two-stage mammography classification model using explainable-AI for ROI detection Nordic Machine Intelligence (NMI), vol. 3, pp. 7 , (ISSN 2703-9196 2703-9196 ), doi: https://doi.org/10.5617/nmi.10459 , 2023. Vitenskapelig artikkel

Olav Brautaset; Ingrid Utseth; Line Eikvil; Arnt-Børre Salberg; Nils Olav Handegard; Learning from weakly labelled marine acoustic data 2023. Vitenskapelig foredrag

Nils Olav Handegard; Leif Bildøy; Olav Brautaset; Tomasz Furmanek; Arne Johannes Holmin; et al. A story about data extraction and deep learning applied to fishery acoustic data 2023. Vitenskapelig foredrag

Olav Brautaset; Ingrid Utseth; Line Eikvil; Arnt-Børre Salberg; Nils Olav Handegard; Learning from weakly labelled marine acoustic data 2023. Poster

Fredrik Andreas Dahl; Marit Holden; Olav Brautaset; Line Eikvil; Utilizing earlier images in mammography cancer detection 2023. Poster

Fredrik Andreas Dahl; Marit Holden; Olav Brautaset; Line Eikvil; Machine learning for screening mammography 2022. Rapport

Ingrid Utseth; Alba Ordonez; Line Eikvil; Olav Brautaset; Arnt Børre Salberg; et al. Improving marine acoustic target classification with context information 2022. Poster

Fredrik Andreas Dahl; Marit Holden; Olav Brautaset; Line Eikvil; A two-stage mammography classification model using XAI for ROI detection 2022. Poster

Nils Olav Handegard; Olav Brautaset; Changkyu Choi; Tomasz Furmanek; Arne Johan Hestnes; et al. Developing and deploying machine learning methods for acoustic data , 2022. Vitenskapelig foredrag

Fredrik Andreas Dahl; Marit Holden; Olav Brautaset; Line Eikvil; A mammography classification model trained from image labels only Proceedings of the Northern Lights Deep Learning Workshop, (ISSN 2703-6928 ), doi: https://doi.org/10.7557/18.6244 , 2022. Vitenskapelig artikkel

Alba Ordonez; Ingrid Utseth; Olav Brautaset; Rolf Korneliussen; Nils Olav Handegard; Evaluation of echosounder data preparation strategies for modern machine learning models Fisheries Research, vol. 254, pp. 8 , (ISSN 0165-7836 1872-6763 ), doi: https://doi.org/10.1016/j.fishres.2022.106411 , 2022. Vitenskapelig artikkel

Line Eikvil; Fredrik Andreas Dahl; Marit Holden; Olav Brautaset; Solveig Hofvind; et al. Procedures for mammographic screening with machine learning 2022. Rapport

Fredrik Andreas Dahl; Marit Holden; Olav Brautaset; Line Eikvil; A mammography classification model trained from image labels only 2022. Poster

Ingrid Utseth; Alba Ordonez; Line Eikvil; Olav Brautaset; Arnt-Børre Salberg; et al. Improving marine acoustic target classification with context information 2021. Poster

Olav Brautaset; Marine Acoustic Classification: Supervised Semantic Segmentation of Echosounder Data using CNNs 2021. Vitenskapelig foredrag

Changkyu Choi; Michael Kampffmeyer; Nils Olav Handegard; Arnt Børre Salberg; Olav Brautaset; et al. Semi-supervised target classification in multi-frequency echosounder data ICES Journal of Marine Science, vol. 78, pp. 2615 2627 12 , (ISSN 1054-3139 1095-9289 ), doi: https://doi.org/10.1093/icesjms/fsab140 , 2021. Vitenskapelig artikkel

Nils Olav Handegard; Lars Nonboe Andersen; Olav Brautaset; Changkyu Choi; Inge Kristian Eliassen; et al. Fisheries acoustics and Acoustic Target Classification - Report from the COGMAR/CRIMAC workshop on machine learning methods in fisheries acoustics , 2021. Rapport

Line Eikvil; Marit Holden; Lars Holden; Olav Brautaset; Machine learning for screening mammography 2021. Rapport

Line Eikvil; Marit Holden; Lars Holden; Olav Brautaset; Machine learning for screening mammography - Initial analyses on a first limited dataset 2020. Rapport

Olav Brautaset; Anders Ueland Waldeland; Espen Johnsen; Ketil Malde; Line Eikvil; et al. Acoustic classification in multifrequency echosounder data using deep convolutional neural networks ICES Journal of Marine Science, vol. 77, pp. 1391 1400 , (ISSN 1054-3139 1095-9289 ), doi: https://doi.org/10.1093/icesjms/fsz235 , 2020. Vitenskapelig artikkel

Olav Brautaset; Automatic target classification using supervised learning on marine acoustic data with auxiliary information 2020. Lecture

Line Eikvil; Alba Ordonez; Olav Brautaset; Feasibility study: Non-verbal communication interpreter - Image-based methodological approaches 2020. Rapport

Olav Brautaset; Automated acoustic data processing with deep learning 2019. Lecture

Olav Brautaset; Automatic fish identification from multi-frequency acoustic data using deep learning 2019. Vitenskapelig foredrag

Olav Brautaset; Applying deep learning to non-standard image data - a case study on marine acoustics 2019. Vitenskapelig foredrag

Olav Brautaset; Nils Olav Handegard; Automated acoustic data processing with deep learning 2019. Vitenskapelig foredrag

Stein Haugen; Nathaniel John Edwin; Olav Brautaset; Jan Erik Vinnem; Quantitative risk analysis for decision support in process plant operations 2016. Vitenskapelig foredrag

Stein Haugen; Nathaniel John Edwin; Jan Erik Vinnem; Olav Brautaset; Ole Magnus Nyheim; et al. Activity-based risk analysis for process plant operations Institution of Chemical Engineers Symposium Series, pp. 12 , , 2016. Vitenskapelig artikkel

Stein Haugen; Jan Erik Vinnem; Olav Brautaset; Rolf Johan Bye; Ole Magnus Nyheim; et al. Risk information for operational decision making in oil and gas operations pp. 405 413 8 , doi: https://doi.org/10.1201/b19094-57 , 2015. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

Stein Haugen; Jan Erik Vinnem; Olav Brautaset; Rolf Johan Bye; Ole Magnus Nyheim; et al. Risk information for operational decision making in oil and gas operations 2015. Vitenskapelig foredrag