Search Results - "Ulfarsson, Magnus Ö."

Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis by Stacey, Simon N., Zink, Florian, Halldorsson, Gisli H., Stefansdottir, Lilja, Gudjonsson, Sigurjon A., Einarsson, Gudmundur, Hjörleifsson, Grimur, Eiriksdottir, Thjodbjorg, Helgadottir, Anna, Björnsdottir, Gyda, Thorgeirsson, Thorgeir E., Olafsdottir, Thorunn A., Jonsdottir, Ingileif, Gretarsdottir, Solveig, Tragante, Vinicius, Magnusson, Magnus K., Jonsson, Hakon, Gudmundsson, Julius, Olafsson, Sigurgeir, Holm, Hilma, Gudbjartsson, Daniel F., Sulem, Patrick, Helgason, Agnar, Thorsteinsdottir, Unnur, Tryggvadottir, Laufey, Rafnar, Thorunn, Melsted, Pall, Ulfarsson, Magnus Ö., Vidarsson, Brynjar, Thorleifsson, Gudmar, Stefansson, Kari

“…Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using…”
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Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network by Palsson, Frosti, Sveinsson, Johannes R., Ulfarsson, Magnus O.

“…In this letter, we propose a method using a 3-D convolutional neural network to fuse together multispectral and hyperspectral (HS) images to obtain a high…”
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A New Pansharpening Algorithm Based on Total Variation by Palsson, Frosti, Sveinsson, Johannes R., Ulfarsson, Magnus O.

“…In this letter, we present a new method for the pansharpening of multispectral satellite imagery. Pansharpening is the process of synthesizing a high spatial…”
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Hyperspectral Unmixing Using a Neural Network Autoencoder by Palsson, Burkni, Sigurdsson, Jakob, Sveinsson, Johannes R., Ulfarsson, Magnus O.

“…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…”
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Blind Hyperspectral Unmixing Using Autoencoders: A Critical Comparison by Palsson, Burkni, Sveinsson, Johannes R., Ulfarsson, Magnus O.

“…Deep learning (DL) has heavily impacted the data-intensive field of remote sensing. Autoencoders are a type of DL methods that have been found to be powerful…”
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Hyperspectral Feature Extraction Using Sparse and Smooth Low-Rank Analysis by Rasti, Behnood, Ghamisi, Pedram, Ulfarsson, Magnus

“…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…”
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Synthesis of Synthetic Hyperspectral Images with Controllable Spectral Variability Using a Generative Adversarial Network by Palsson, Burkni, Ulfarsson, Magnus O., Sveinsson, Johannes R.

“…In hyperspectral unmixing (HU), spectral variability in hyperspectral images (HSIs) is a major challenge which has received a lot of attention over the last…”
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Sparse Distributed Multitemporal Hyperspectral Unmixing by Sigurdsson, Jakob, Ulfarsson, Magnus O., Sveinsson, Johannes R., Bioucas-Dias, Jose M.

“…Blind hyperspectral unmixing jointly estimates spectral signatures and abundances in hyperspectral images (HSIs). Hyperspectral unmixing is a powerful tool for…”
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Fusing Sentinel-2 and Landsat 8 Satellite Images Using a Model-Based Method by Sigurdsson, Jakob, Armannsson, Sveinn E., Ulfarsson, Magnus O., Sveinsson, Johannes R.

“…The Copernicus Sentinel-2 (S2) constellation comprises of two satellites in a sun-synchronous orbit. The S2 sensors have three spatial resolutions: 10, 20, and…”
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Spectral-Spatial Hyperspectral Unmixing Using Multitask Learning by Palsson, Burkni, Sveinsson, Johannes R., Ulfarsson, Magnus O.

“…Hyperspectral unmixing is an important and challenging task in the field of remote sensing which arises when the spatial resolution of sensors is insufficient…”
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Unsupervised and Supervised Feature Extraction Methods for Hyperspectral Images Based on Mixtures of Factor Analyzers by Zhao, Bin, Ulfarsson, Magnus O., Sveinsson, Johannes R., Chanussot, Jocelyn

“…This paper proposes three feature extraction (FE) methods based on density estimation for hyperspectral images (HSIs). The methods are a mixture of factor…”
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Predicting Classification Performance for Benchmark Hyperspectral Datasets by Zhao, Bin, Ragnarsson, Haukur Isfeld, Ulfarsson, Magnus O., Cavallaro, Gabriele, Benediktsson, Jon Atli

“…The classification of hyperspectral images (HSIs) is an essential application of remote sensing and it is addressed by numerous publications every year. A…”
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Sentinel-2 Sharpening Using a Single Unsupervised Convolutional Neural Network With MTF-Based Degradation Model by Nguyen, Han V., Ulfarsson, Magnus O., Sveinsson, Johannes R., Mura, Mauro Dalla

“…The Sentinel-2 (S2) constellation provides multispectral images at 10 m, 20 m, and 60 m resolution bands. Obtaining all bands at 10 m resolution would benefit…”
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Convolutional Autoencoder for Spectral-Spatial Hyperspectral Unmixing by Palsson, Burkni, Ulfarsson, Magnus O., Sveinsson, Johannes R.

“…Blind hyperspectral unmixing is the process of expressing the measured spectrum of a pixel as a combination of a set of spectral signatures called endmembers…”
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Predicting the probability of death using proteomics by Eiriksdottir, Thjodbjorg, Ardal, Steinthor, Jonsson, Benedikt A., Lund, Sigrun H., Ivarsdottir, Erna V., Norland, Kristjan, Ferkingstad, Egil, Stefansson, Hreinn, Jonsdottir, Ingileif, Holm, Hilma, Rafnar, Thorunn, Saemundsdottir, Jona, Norddahl, Gudmundur L., Thorgeirsson, Gudmundur, Gudbjartsson, Daniel F., Sulem, Patrick, Thorsteinsdottir, Unnur, Stefansson, Kari, Ulfarsson, Magnus O.

“…Predicting all-cause mortality risk is challenging and requires extensive medical data. Recently, large-scale proteomics datasets have proven useful for…”
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Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural Networks by Nguyen, Han V., Ulfarsson, Magnus O., Sveinsson, Johannes R.

“…Hyperspectral images (HSIs) are useful for many remote sensing applications. However, they are usually affected by noise that degrades the HSIs quality…”
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Model-Based Reduced-Rank Pansharpening by Palsson, Frosti, Ulfarsson, Magnus O., Sveinsson, Johannes R.

“…Observation of the Earth using satellites mounted with optical sensors is an important application of remote sensing. Owing to physical constraints,…”
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Hyperspectral Image Denoising Using Spectral-Spatial Transform-Based Sparse and Low-Rank Representations by Zhao, Bin, Ulfarsson, Magnus O., Sveinsson, Johannes R., Chanussot, Jocelyn

“…This article proposes a denoising method based on sparse spectral-spatial and low-rank representations (SSSLRR) using the 3-D orthogonal transform (3-DOT)…”
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Sentinel-2 Sharpening Using a Reduced-Rank Method by Ulfarsson, Magnus O., Palsson, Frosti, Dalla Mura, Mauro, Sveinsson, Johannes R.

“…Recently, the Sentinel-2 (S2) satellite constellation was deployed for mapping and monitoring the Earth environment. Images acquired by the sensors mounted on…”
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Large-scale plasma proteomics comparisons through genetics and disease associations by Eldjarn, Grimur Hjorleifsson, Ferkingstad, Egil, Lund, Sigrun H., Helgason, Hannes, Magnusson, Olafur Th, Gunnarsdottir, Kristbjorg, Olafsdottir, Thorunn A., Halldorsson, Bjarni V., Olason, Pall I., Zink, Florian, Gudjonsson, Sigurjon A., Sveinbjornsson, Gardar, Magnusson, Magnus I., Helgason, Agnar, Oddsson, Asmundur, Halldorsson, Gisli H., Magnusson, Magnus K., Saevarsdottir, Saedis, Eiriksdottir, Thjodbjorg, Masson, Gisli, Stefansson, Hreinn, Jonsdottir, Ingileif, Holm, Hilma, Rafnar, Thorunn, Melsted, Pall, Saemundsdottir, Jona, Norddahl, Gudmundur L., Thorleifsson, Gudmar, Ulfarsson, Magnus O., Gudbjartsson, Daniel F., Thorsteinsdottir, Unnur, Sulem, Patrick, Stefansson, Kari

“…High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the…”
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