Opin vísindi

Fletta eftir höfundi "Ulfarsson, Magnus"

Fletta eftir höfundi "Ulfarsson, Magnus"

Röðun: Raða: Niðurstöður:

  • Icon
    15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia 
    Ulfarsson, Magnus; Walters, G B; Gústafsson, O; Steinberg, S; Silva, A; Doyle, O M; Brammer, M; Gudbjartsson, Daniel; Arnarsdóttir, S; Jonsdottir, Gudbjorg; Gísladóttir, R S; Bjornsdottir, Gyda; Helgason, H; Ellingsen, L M; Halldórsson, J G; Sæmundsen, Evald E.; Stefánsdóttir, B; Jónsson, L; Eiríksdóttir, V K; Eiríksdóttir, G R; Jóhannesdóttir, G H; Unnsteinsdóttir, U; Jónsdóttir, B; Magnúsdóttir, B B; sulem, patrick; Þorsteinsdóttir, Unnur; Sigurðsson, E; Brandeis, D; Meyer-Lindenberg, A; Stefánsson, H; Stefansson, Kari (Springer Nature, 2017-04-25)
    Several copy number variants have been associated with neuropsychiatric disorders and these variants have been shown to also influence cognitive abilities in carriers unaffected by psychiatric disorders. Previously, we associated the 15q11.2(BP1–BP2) ...
  • Icon
    The 2014–2015 Lava Flow Field at Holuhraun, Iceland: Using Airborne Hyperspectral Remote Sensing for Discriminating the Lava Surface 
    Aufaristama, Muhammad; Höskuldsson, Ármann; Ulfarsson, Magnus; Jónsdóttir, Ingibjörg; Thordarson, Thorvaldur (MDPI AG, 2019-02-26)
    The Holuhraun lava flow was the largest effusive eruption in Iceland for 230 years, with an estimated lava bulk volume of ~1.44 km3 and covering an area of ~84 km2. The six month long eruption at Holuhraun 2014–2015 generated a diverse surface environment. ...
  • Icon
    Brain age prediction using deep learning uncovers associated sequence variants 
    Jónsson, Benedikt Atli; Bjornsdottir, Gyda; Thorgeirsson, Thorgeir; Ellingsen, Lotta María; Walters, G. Bragi; Gudbjartsson, Daniel; Stefansson, Hreinn; Stefansson, Kari; Ulfarsson, Magnus (Springer Science and Business Media LLC, 2019-11-27)
    Machine learning algorithms can be trained to estimate age from brain structural MRI. The difference between an individual’s predicted and chronological age, predicted age difference (PAD), is a phenotype of relevance to aging and brain disease. Here, ...
  • Icon
    Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia 
    Sønderby, Ida E; Ulfarsson, Magnus; Walters, G. Bragi; Stefansson, Kari (Springer Science and Business Media LLC, 2018-10-03)
    Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes ...
  • Icon
    Hyperspectral Feature Extraction Using Sparse and Smooth Low-Rank Analysis 
    Rasti, Behnood; Ghamisi, Pedram; Ulfarsson, Magnus (MDPI AG, 2019-01-10)
    In this paper, we develop a hyperspectral feature extraction method called sparse and smooth low-rank analysis (SSLRA). First, we propose a new low-rank model for hyperspectral images (HSIs) where we decompose the HSI into smooth and sparse components. ...
  • Icon
    Hyperspectral Unmixing Using a Neural Network Autoencoder 
    Palsson, Burkni; Sigurdsson, Jakob; Sveinsson, Jóhannes Rúnar; Ulfarsson, Magnus (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    In this paper, we present a deep learning based method for blind hyperspectral unmixing in the form of a neural network autoencoder. We show that the linear mixture model implicitly puts certain architectural constraints on the network, and it effectively ...
  • Icon
    Lava Flow Roughness on the 2014–2015 Lava Flow-Field at Holuhraun, Iceland, Derived from Airborne LiDAR and Photogrammetry 
    Aufaristama, Muhammad; Höskuldsson, Ármann; Ulfarsson, Magnus; Jónsdóttir, Ingibjörg; Thordarson, Thorvaldur (MDPI AG, 2020-03-31)
    Roughness can be used to characterize the morphologies of a lava flow. It can be used to identify lava flow features, provide insight into eruption conditions, and link roughness pattern across a lava flow to emplacement conditions. In this study, we ...
  • Icon
    MAP1B mutations cause intellectual disability and extensive white matter deficit 
    Walters, G. Bragi; Gústafsson, Ómar; Sveinbjornsson, Gardar; Eiriksdottir, Valgerdur Kristin; Ágústsdóttir, Arna B.; Jónsdóttir, Guðrún A.; Steinberg, Stacy; Gunnarsson, Árni F.; Magnússon, Magnús I.; Unnsteinsdóttir, Unnur; Lee, Amy L.; Jónasdóttir, Aðalbjörg; Sigurðsson, Ásgeir; Jónasdóttir, Áslaug; Skúladóttir, Ástrós; Jonsson, Lina; Nawaz, Muhammad S.; sulem, patrick; Frigge, Mike; Ingason, Andrés; Love, Askell; Norðdahl, Guðmundur L.; Zervas, Mark; Gudbjartsson, Daniel; Ulfarsson, Magnus; Sæmundsen, Evald E.; Stefansson, Hreinn; Stefansson, Kari (Springer Science and Business Media LLC, 2018-08-27)
    Discovery of coding variants in genes that confer risk of neurodevelopmental disorders is an important step towards understanding the pathophysiology of these disorders. Wholegenome sequencing of 31,463 Icelanders uncovers a frameshift variant ...
  • Icon
    New Insights for Detecting and Deriving Thermal Properties of Lava Flow Using Infrared Satellite during 2014–2015 Effusive Eruption at Holuhraun, Iceland 
    Aufaristama, Muhammad; Höskuldsson, Ármann; Jónsdóttir, Ingibjörg; Ulfarsson, Magnus; Thordarson, Thorvaldur (MDPI AG, 2018-01-20)
    A new lava field was formed at Holuhraun in the Icelandic Highlands, north of Vatnajökull glacier, in 2014–2015. It was the largest effusive eruption in Iceland for 230 years, with an estimated lava bulk volume of ~1.44 km3 covering an area of ~84 km2. ...
  • Icon
    Reciprocal White Matter Changes Associated With Copy Number Variation at 15q11.2 BP1-BP2: A Diffusion Tensor Imaging Study 
    Silva, Ana I.; Ulfarsson, Magnus; Stefansson, Hreinn; Gústafsson, Ómar; Walters, G. Bragi; Linden, David E.J.; Wilkinson, Lawrence S.; Drakesmith, Mark; Owen, Michael J.; Hall, Jeremy; Stefansson, Kari (Elsevier BV, 2019-04-01)
    Background: The 15q11.2 BP1-BP2 cytogenetic region has been associated with learning and motor delays, autism, and schizophrenia. This region includes a gene that codes for the cytoplasmic FMR1 interacting protein 1 (CYFIP1). The CYFIP1 protein is ...
  • Icon
    Sentinel-2 Image Fusion Using a Deep Residual Network 
    Palsson, Frosti; Sveinsson, Jóhannes Rúnar; Ulfarsson, Magnus (MDPI AG, 2018-08-15)
    Single sensor fusion is the fusion of two or more spectrally disjoint reflectance bands that have different spatial resolution and have been acquired by the same sensor. An example is Sentinel-2, a constellation of two satellites, which can acquire ...
  • Icon
    Spectral–Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields 
    Benediktsson, Jon Atli; Ulfarsson, Magnus; Ghamisi, Pedram (IEEE, 2014)
    Hyperspectral remote sensing technology allows one to acquire a sequence of possibly hundreds of contiguous spectral images from ultraviolet to infrared. Conventional spectral classifiers treat hyperspectral images as a list of spectral measurements ...
  • Icon
    Thermal model of lava in Mt. Agung during December 2017 episodes derived from Integrated SENTINEL 2A and ASTER remote sensing datasets 
    Aufaristama, Muhammad; Höskuldsson, Ármann; Jónsdóttir, Ingibjörg; Ulfarsson, Magnus; Erlangga, I G D; Thordarson, Thorvaldur (IOP Publishing, 2019-08-14)
    In the beginning of December 2017, Mt. Agung eruption powered down to minor ash emissions and on the middle of December, aerial photographs of the crater were taken by Indonesia Centre of Volcanology and Geological Hazard Mitigation (PVMBG) showing a ...
  • Icon
    Unsupervised and Supervised Feature Extraction Methods for Hyperspectral Images Based on Mixtures of Factor Analyzers 
    Zhao, Bin; Ulfarsson, Magnus; Sveinsson, Jóhannes Rúnar; Chanussot, Jocelyn (MDPI AG, 2020-04-07)
    This paper proposes three feature extraction (FE) methods based on density estimation for hyperspectral images (HSIs). The methods are a mixture of factor analyzers (MFA), deep MFA (DMFA), and supervised MFA (SMFA). The MFA extends the Gaussian mixture ...