Publikasjoner fra Cristin: Recent submissions
Now showing items 221-240 of 288
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Transcriptomic signals in blood prior to lung cancer focusing on time to diagnosis and metastasis
(Journal article; Peer reviewed, 2021) -
Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective
(Journal article; Peer reviewed, 2021) -
Fisheries acoustics and Acoustic Target Classification - Report from the COGMAR/CRIMAC workshop on machine learning methods in fisheries acoustics
(Rapport fra havforskningen;, Research report, 2021)This report documents a workshop organised by the COGMAR and CRIMAC projects. The objective of the workshop was twofold. The first objective was to give an overview of ongoing work using machine learning for Acoustic Target ... -
Preservation of Trust in Long-Term Records Management Systems
(Report at the Norwegian Computing Center;, Research report, 2008) -
A combined estimate of global temperature
(NR-notat;, Research report, 2021) -
Vurdering av tiltak mot lakselus i PO3, for reduksjon av smittepress
(NR-notat;, Research report, 2021) -
Evaluation of CMIP5 and CMIP6 simulations of historical surface air temperature extremes using proper evaluation methods
(Journal article; Peer reviewed, 2020)Reliable projections of extremes by climate models are becoming increasingly important in the context of climate change and associated societal impacts. Extremes are by definition rare events, characterized by a small ... -
Spatial scaling of population synchrony in marine fish depends on their life history
(Journal article; Peer reviewed, 2019)The synchrony of population dynamics in space has important implications for ecological processes, for example affecting the spread of diseases, spatial distributions and risk of extinction. Here, we studied the relationship ... -
A Systematic Mapping Study on Cyber Security Indicator Data
(Journal article; Peer reviewed, 2021) -
Final report for the REDUS project - Reduced Uncertainty in Stock Assessment
(Rapport fra havforskningen;, Research report, 2021)The REDUS project (2016-2020) has been a strategic project at the Institute of Marine Research (IMR) aimed at quantifying and reducing the uncertainty in data-rich and age-structured stock assessments (e.g., cod, herring, ... -
Teknologi og inkludering av personer med nedsatt syn i arbeidslivet: Kunnskapsoppsummering
(Report at the Norwegian Computing Center;, Research report, 2021) -
Pairwise local Fisher and naive Bayes: Improving two standard discriminants
(Journal article; Peer reviewed, 2020)The Fisher discriminant is probably the best known likelihood discriminant for continuous data. Another benchmark discriminant is the naive Bayes, which is based on marginals only. In this paper we extend both discriminants ... -
iStøtet – IT-støtte for synshemmede eldre 2020: Inkludering i informasjonssamfunnet – motivasjon, opplæring og oppfølging
(Report at the Norwegian Computing Center;, Research report, 2021)Synshemmede eldre er en gruppe med stor risiko for å oppleve ensomhet. Bruk av smartteknologi blant denne gruppen er lavere enn blant seende eldre, samtidig som nytten kan være større. Det å beherske smartteknologi kan ... -
iStøtet – IT-støtte for synshemmede eldre
(Report at the Norwegian Computing Center;, Research report, 2020)Synshemmede eldre er en gruppe med stor risiko for å oppleve ensomhet. Bruk av smartteknologi blant denne gruppen er lavere enn blant seende eldre, samtidig som nytten kan være større. Det å beherske smartteknologi kan ... -
Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series
(Journal article; Peer reviewed, 2020) -
Self-Constructing Graph Convolutional Networks for Semantic Labeling
(Chapter, 2020)Graph Neural Networks (GNNs) have received increasing attention in many fields. However, due to the lack of prior graphs, their use for semantic labeling has been limited. Here, we propose a novel architecture called the ... -
Multi-View Self-Constructing Graph Convolutional Networks With Adaptive Class Weighting Loss for Semantic Segmentation
(Chapter, 2020)We propose a novel architecture called the Multi-view Self-Constructing Graph Convolutional Networks (MSCG-Net) for semantic segmentation. Building on the recently proposed Self-Constructing Graph (SCG) module, which makes ... -
Estimating Traffic in Urban Areas from Very-High Resolution Aerial Images
(Journal article; Peer reviewed, 2021)Traffic estimation from very-high-resolution remote-sensing imagery has received increasing interest during the last few years. In this article, we propose an automatic system for estimation of the annual average daily ...