A database for publications published by researchers and students at SimulaMet.
Research area
Publication type
- All (1059)
- Journal articles (300)
- Books (9)
- Edited books (3)
- Proceedings, refereed (339)
- Book chapters (13)
- Talks, keynote (25)
- PhD theses (10)
- Proceedings, non-refereed (19)
- Posters (18) Remove Posters <span class="counter">(18)</span> filter
- Technical reports (15)
- Manuals (1)
- Talks, invited (191)
- Talks, contributed (31)
- Public outreach (62)
- Master's theses (1)
- Miscellaneous (22)
Posters
A decade of evolution in telecommunications infrastructure
In Poster: A decade of evolution in telecommunications infrastructure. IMC 21: IMC , 2021.Status: Published
A decade of evolution in telecommunications infrastructure
Characterizing countries’ standing in terms of the maturity of their telecommunications infrastructure is paramount to inform policy and investments. Here, we use a broad set of features to group countries according to the state of their infrastructures and track how this has changed between 2010 and 2020. While a few nations continue to dominate, the membership of this club has changed with several European countries leaving
Afilliation | Communication Systems |
Project(s) | GAIA, The Center for Resilient Networks and Applications |
Publication Type | Poster |
Year of Publication | 2021 |
Secondary Title | Poster: A decade of evolution in telecommunications infrastructure |
Date Published | 10/2021 |
Publisher | IMC |
Place Published | IMC 21 |
Type of Work | Internet measurements |
An Optimization Framework for Regularized Linearly Coupled Matrix-Tensor Factorization
2020 28th European Signal Processing Conference (EUSIPCO), Amsterdam, Netherlands, 2021.Status: Published
An Optimization Framework for Regularized Linearly Coupled Matrix-Tensor Factorization
Afilliation | Machine Learning |
Project(s) | Department of Data Science and Knowledge Discovery |
Publication Type | Poster |
Year of Publication | 2021 |
Place Published | 2020 28th European Signal Processing Conference (EUSIPCO), Amsterdam, Netherlands |
Anomaly Detection in Optical Links Using State of Polarization Monitoring
2021 Joint European Conference on Networks and Communications & 6G Summit, Porto, Portugal, 2021.Status: Published
Anomaly Detection in Optical Links Using State of Polarization Monitoring
Afilliation | Communication Systems |
Project(s) | GAIA, The Center for Resilient Networks and Applications |
Publication Type | Poster |
Year of Publication | 2021 |
Place Published | 2021 Joint European Conference on Networks and Communications & 6G Summit, Porto, Portugal |
Keywords | Anomaly detection, Machine learning, Optical Fibre, State of Polarization |
URL | https://www.eucnc.eu/poster-a/ |
Assessment of sperm motility according to WHO classification using convolutional neural networks
ESHRE: ESHRE, 2021.Status: Accepted
Assessment of sperm motility according to WHO classification using convolutional neural networks
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Poster |
Year of Publication | 2021 |
Publisher | ESHRE |
Place Published | ESHRE |
Posters
A Framework for Interaction-based Propagation Analysis in Online Social Networks
Complex Networks, 2020.Status: Published
A Framework for Interaction-based Propagation Analysis in Online Social Networks
Afilliation | Scientific Computing |
Project(s) | Department of High Performance Computing , Department of Holistic Systems, UMOD: Understanding and Monitoring Digital Wildfires |
Publication Type | Poster |
Year of Publication | 2020 |
Place Published | Complex Networks |
Posters
Automatic Thumbnail Selection for Soccer using Machine Learning
NORA Annual Conference, Stavanger, Norway, 2022.Status: Accepted
Automatic Thumbnail Selection for Soccer using Machine Learning
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Poster |
Year of Publication | 2022 |
Place Published | NORA Annual Conference, Stavanger, Norway |
Characterizing postprandial metabolic response using multi-way data analysis
Norwegian Bioinformatics Days, 2022.Status: Published
Characterizing postprandial metabolic response using multi-way data analysis
Analysis of time-resolved postprandial metabolomics data can enhance our knowledge about the human metabolism by providing a better understanding of regulation of subgroups of metabolites (e.g., lipids) and variations in postprandial responses of subgroups of people, with the potential to ultimately advance precision medicine. However, characterizing postprandial metabolomics response and understanding group differences is a challenging task since it requires the analysis of large-scale metabolomics data from a large set of individuals containing measurements of a wide set of metabolites at multiple time points. Such data is in the form of a three-way array: subjects by metabolites by time points. The state-of-the-art analysis methods mainly focus on clustering temporal profiles relying on summaries of the data across subjects or univariate analysis techniques studying one metabolite at a time, and fail to associate subgroups of subjects and subsets of metabolites with the dynamic time profile simultaneously.
In this study, we use NMR (nuclear magnetic resonance) spectroscopy measurements of plasma samples (of over three hundred individuals from the COPSAC2000 cohort) collected at multiple time points during a challenge test. We use a multi-way analysis technique called the CANDECOMP/PARAFAC (CP) model to extract interpretable patterns from the time-resolved data. We compare the analysis of postprandial data, fasting state-corrected data and only fasting state data, and demonstrate the differences between different analysis approaches.
Our results show that the CP model reveals biologically meaningful patterns capturing how certain metabolite groups and their temporal profiles relate to various meta variables, in particular, BMI (body mass index), confirming already known biological knowledge as well as revealing new biological insights.
Afilliation | Machine Learning |
Project(s) | TrACEr: Time-Aware ConstrainEd Multimodal Data Fusion, Department of Data Science and Knowledge Discovery |
Publication Type | Poster |
Year of Publication | 2022 |
Place Published | Norwegian Bioinformatics Days |
Keywords | CANDECOMP/PARAFAC, Dynamic metabolomics data, large-scale dataset, Tensor factorization |
Posters
Concept Explanations for Deep Learning-Based Diabetic Retinopathy Diagnosis
Nordic AI Meet 2023, 2023.Status: Accepted
Concept Explanations for Deep Learning-Based Diabetic Retinopathy Diagnosis
Diabetic retinopathy (DR) is a common complication of diabetes that damages the eye and potentially leads to blindness. The severity and treatment choice of DR depends on the presence of medical findings in fundus images. Much work has been done in developing complex machine learning (ML) models to automatically diagnose DR from fundus images. However, their high level of complexity increases the demand for techniques improving human understanding of the ML models. Explainable artificial intelligence (XAI) methods can detect weaknesses in ML models and increase trust among end users. In the medical field, it is crucial to explain ML models in order to apply them in the clinic. While a plethora of XAI methods exists, heatmaps are typically applied for explaining ML models for DR diagnosis. Heatmaps highlight image areas that are regarded as important for the model when making a prediction. Even though heatmaps are popular, they can be less appropriate in the medical field. Testing with Concept Activation Vectors (TCAV), providing explanations based on human-friendly concepts, can be a more suitable alternative for explaining models for DR diagnosis, but it has not been thoroughly investigated for DR models. We develop a deep neural network for diagnosing DR from fundus images and apply TCAV for explaining the resulting model. Concept generation with and without masking is compared. Based on diagnostic criteria for DR, we evaluate the model’s concept ranking for different severity levels of DR. TCAV can explain individual images to gain insight into a specific case, or an entire class to evaluate overall consistency with diagnostic standards. The most important concepts for the DR model agree with diagnostic criteria for DR. No large differences are detected between the two concept generation approaches. TCAV is a flexible explanation method where human-friendly concepts provide insights and trust in ML models for medical image analyses, and it shows promising results for DR grading.
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Poster |
Year of Publication | 2023 |
Place Published | Nordic AI Meet 2023 |
Keywords | concept-based explanations, diabetic retinopathy, Explainable artificial intelligence |
Posters
Efficient Processing of Medical Videos in a Multi-auditory Environment Using Gpu Lending
NVIDIA's GPU Technology Conference (GTC), 2019.Status: Published
Efficient Processing of Medical Videos in a Multi-auditory Environment Using Gpu Lending
Afilliation | Software Engineering |
Project(s) | No Simula project, Department of Holistic Systems |
Publication Type | Poster |
Year of Publication | 2019 |
Place Published | NVIDIA's GPU Technology Conference (GTC) |
Posters
Evaluation of DASH Rate Adaptation Algorithms in Operational Mobile Networks
Dublin, Ireland, 2017.Status: Published
Evaluation of DASH Rate Adaptation Algorithms in Operational Mobile Networks
In this study, we evaluate the performance of different Dynamic Adaptive Streaming over HTTP (DASH) video rate adaptation algorithms over mobile networks. More specifically, we compare and evaluate the performance of Basic, Segment Aware Rate Adaptation (SARA), and Buffer-Based Rate Adaptation (BBA) rate adaptation algorithms over the 4G-Long Term Evolution (LTE) networks of three Mobile Network Operators (MNOs): Telenor, Telia, and ICE. We use the Measuring Mobile Broadband Networks in Europe (MONROE) testbed for conducting measurements, and OpenVQ toolbox for evaluation.
Afilliation | Communication Systems |
Project(s) | MONROE: Measuring Mobile Broadband Networks in Europe |
Publication Type | Poster |
Year of Publication | 2017 |
Date Published | 06/2017 |
Place Published | Dublin, Ireland |