A database for publications published by researchers and students at SimulaMet.
Research area
Publication type
- All (362)
- Journal articles (132)
- Books (2)
- Edited books (1)
- Proceedings, refereed (162) Remove Proceedings, refereed <span class="counter">(162)</span> filter
- Book chapters (6)
- Talks, keynote (1)
- PhD theses (5)
- Proceedings, non-refereed (2)
- Posters (7)
- Talks, invited (18)
- Talks, contributed (15)
- Public outreach (3)
- Miscellaneous (8)
Proceedings, refereed
Detecting human embryo cleavage stages using YOLO v5 object detection algorithm
In Nordic Artificial Intelligence Research and Development. Springer, 2023.Status: Published
Detecting human embryo cleavage stages using YOLO v5 object detection algorithm
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | Nordic Artificial Intelligence Research and Development |
Pagination | 81-93 |
Publisher | Springer |
Multimedia datasets: challenges and future possibilities
In International conference on multimedia modeling, 2023.Status: Accepted
Multimedia datasets: challenges and future possibilities
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | International conference on multimedia modeling |
PARAFAC2-based coupled Matrix and Tensor Factorizations
In ICASSP , 2023.Status: Accepted
PARAFAC2-based coupled Matrix and Tensor Factorizations
Afilliation | Machine Learning |
Project(s) | Department of Data Science and Knowledge Discovery , TrACEr: Time-Aware ConstrainEd Multimodal Data Fusion |
Publication Type | Proceedings, refereed |
Year of Publication | 2023 |
Conference Name | ICASSP |
Proceedings, refereed
Unsupervised Image Segmentation via Self-Supervised Learning Image Classification
In MediaEval 2021. Working Notes Proceedings of the MediaEval 2021 Workshop ed. CEUR Workshop Proceedings, 2022.Status: Published
Unsupervised Image Segmentation via Self-Supervised Learning Image Classification
This paper presents the submission of team Medical-XAI for the Medico: Transparency in Medical Image Segmentation task held at MediaEval 2021. We propose an unsupervised method that utilizes tools from the field of explainable artificial intelligence to create segmentation masks. We extract heat maps, which are useful in order to explain how the `black box' model predicts the category of a certain image, and the segmentation masks are directly derived from the heat maps. Our results show that the created masks can capture the relevant findings to a certain extent using only a small amount of image-level labeled data for the classification model and no segmentation masks at all for the training. This is promising for addressing different challenges within the intersection of artificial intelligence for medicine such as availability of data, cost of labeling and interpretable and explainable results.
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | MediaEval 2021 |
Edition | Working Notes Proceedings of the MediaEval 2021 Workshop |
Publisher | CEUR Workshop Proceedings |
Keywords | clustering, Explainable artificial intelligence, Global Features, Grad-CAM, Image segmentation, Medical imaging, Polyp Detection, Self-supervised learning |
URL | http://ceur-ws.org/Vol-3181/ |
Multi-task FMRI Data Fusion using IVA and PARAFAC2
In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022.Status: Published
Multi-task FMRI Data Fusion using IVA and PARAFAC2
Afilliation | Machine Learning |
Project(s) | Department of Data Science and Knowledge Discovery , TrACEr: Time-Aware ConstrainEd Multimodal Data Fusion |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Pagination | 1466-1470 |
Publisher | IEEE |
DOI | 10.1109/ICASSP43922.2022.9747662 |
Neighborhood Graph Neural Networks under Random Perturbations and Quantization Errors
In IEEE International Conference on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2022.Status: Published
Neighborhood Graph Neural Networks under Random Perturbations and Quantization Errors
Afilliation | Machine Learning |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | IEEE International Conference on Signal Processing Advances in Wireless Communications (SPAWC) |
Publisher | IEEE |
Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the IKTPLUSS DEEPCOBOT grant 306640/O70 from the Research Council of Norway. |
DOI | 10.1109/SPAWC51304.2022.9834020 |
Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications
In IEEE International Conference on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2022.Status: Published
Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications
Afilliation | Machine Learning |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | IEEE International Conference on Signal Processing Advances in Wireless Communications (SPAWC) |
Publisher | IEEE |
Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the FRIPRO TOPPFORSK WISECART grant 250910/F20 from the Research Council of Norway. |
Joint Learning of Topology and Invertible Nonlinearities from Multiple Time Series
In IEEE International Conference on Machine Learning, Optimization, and Data Science (ISMODE), 2022.Status: Accepted
Joint Learning of Topology and Invertible Nonlinearities from Multiple Time Series
Afilliation | Machine Learning |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | IEEE International Conference on Machine Learning, Optimization, and Data Science (ISMODE) |
Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the IKTPLUSS INDURB grant 270730/O70 and the SFI Offshore Mechatronics grant 237896/O30 from the Research Council of Norway. |
Online Joint Nonlinear Topology Identification and Missing Data Imputation over Dynamic Graphs
In 30th European Signal Processing Conference (EUSIPCO). IEEE, 2022.Status: Published
Online Joint Nonlinear Topology Identification and Missing Data Imputation over Dynamic Graphs
Extracting causal graph structures from multivariate time series, termed topology identification, is a fundamental problem in network science with several important applications. Topology identification is a challenging problem in real-world sensor networks, especially when the available time series are partially observed due to faulty communication links or sensor failures. The problem becomes even more challenging when the sensor dependencies are nonlinear and nonstationary. This paper proposes a kernel-based online framework using random feature approximation to jointly estimate nonlinear causal dependencies and missing data from partial observations of streaming graph-connected time series. Exploiting the fact that real-world networks often exhibit sparse topologies, we propose a group lasso-based optimization framework for topology identification, which is solved online using alternating minimization techniques. The ability of the algorithm is illustrated using several numerical experiments conducted using both synthetic and real data.
Afilliation | Machine Learning |
Project(s) | Signal and Information Processing for Intelligent Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | 30th European Signal Processing Conference (EUSIPCO) |
Publisher | IEEE |
Notes | This work is a joint collaboration between SimulaMet and University of Agder. This work was supported by the IKTPLUSS INDURB grant 270730/O70 and the SFI Offshore Mechatronics grant 237896/O30 from the Research Council of Norway. |
Unequal Covariance Awareness for Fisher Discriminant Analysis and Its Variants in Classification
In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022.Status: Published
Unequal Covariance Awareness for Fisher Discriminant Analysis and Its Variants in Classification
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | 2022 International Joint Conference on Neural Networks (IJCNN) |
Pagination | 1-8 |
Publisher | IEEE |