Blar i tittel Artikler, rapporter og annet (fysikk og teknologi)

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    • A K-Wishart Markov random field model for clustering of polarimetric SAR imagery 

      Akbari, Vahid; Moser, Gabriele; Doulgeris, Anthony Paul; Anfinsen, Stian Normann; Eltoft, Torbjørn; Serpico, Sebastian Bruno (Peer reviewed; Bokkapittel; Bok; Book; Chapter, 2011-10-20)
      A clustering method that combines an advanced statistical distribution with spatial contextual information is proposed for multilook polarimetric synthetic aperture radar (PolSAR) data. It is based on a Markov random field (MRF) model that integrates a K-Wishart distribution for the PolSAR data statistics conditioned to each image cluster and a Potts model for the spatial context. Specifically, the ...

    • A K-Wishart Markov random field model for clustering of polarimetric SAR imagery 

      Moser, Gabriele; Akbari, Vahid; Eltoft, Torbjørn; Doulgeris, Anthony Paul; Anfinsen, Stian Normann; Sebastian, Serpico (Conference object; Konferansebidrag, 2011)

    • K2 Campaign 5 observations of pulsating subdwarf B stars: Binaries and super-Nyquist frequencies 

      Reed, Michael D; Armbrecht, EL; Telting, John H; Baran, Andrzej S; Østensen, Roy; Blay, Pere; Kvammen, Andreas; Kuutma, Teet; Pursimo, Tapio; Ketzer, Laura; Jeffery, C. Simon (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-12-05)
      We report the discovery of three pulsating subdwarf B stars in binary systems observed with the <i>Kepler</i> space telescope during Campaign 5 of K2. EPIC 211696659 (SDSS J083603.98+155216.4) is a g-mode pulsator with a white dwarf companion and a binary period of 3.16 d. EPICs 211823779 (SDSS J082003.35+173914.2) and 211938328 (LB 378) are both p-mode pulsators with main-sequence F companions. The ...

    • KAIRA Science Results 

      McKay, Derek (Conference object; Konferansebidrag, 2018)

    • A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs 

      Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; Jenssen, Robert (Chapter; Bokkapittel, 2020)
      A large fraction of the electronic health records (EHRs) consists of clinical measurements collected over time, such as lab tests and vital signs, which provide important information about a patient’s health status. These sequences of clinical measurements are naturally represented as time series, characterized by multiple variables and large amounts of missing data, which complicate the analysis. ...

    • The Kernelized Taylor Diagram 

      Wickstrøm, Kristoffer; Johnson, Juan Emmanuel; Løkse, Sigurd Eivindson; Camps-Valls, Gusatu; Mikalsen, Karl Øyvind; Kampffmeyer, Michael; Jenssen, Robert (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-02)
      This paper presents the kernelized Taylor diagram, a graphical framework for visualizing similarities between data populations. The kernelized Taylor diagram builds on the widely used Taylor diagram, which is used to visualize similarities between populations. However, the Taylor diagram has several limitations such as not capturing non-linear relationships and sensitivity to outliers. To address ...

    • Knowledge Gaps and Impact of Future Satellite Missions to Facilitate Monitoring of Changes in the Arctic Ocean 

      Lucas, Sylvain; Johannessen, Johnny Andre; Cancet, Mathilde; Pettersson, Lasse H; Esau, Igor; Rheinlænder, Jonathan Winfield; Ardhuin, Fabrice; Chapron, Bertrand; Korosov, Anton; Collard, Fabrice; Herlédan, Sylvain; Olason, Einar; Ferrari, Ramiro; Fouchet, Ergane; Donlon, Craig (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-30)
      Polar-orbiting satellite observations are of fundamental importance to explore the main scientific challenges in the Arctic Ocean, as they provide information on bio-geo-physical variables with a denser spatial and temporal coverage than in-situ instruments in such a harsh and inaccessible environment. However, they are limited by the lack of coverage near the North Pole (Polar gap), the polar night, ...

    • Label-free imaging on waveguide platform with enhanced resolution and contrast 

      Jayakumar, Nikhil; Dullo, Firehun Tsige; Dubey, Vishesh Kumar; Ahmad, Azeem; Cauzzo, Jennifer; Mazagao Guerreiro, Eduarda; Snir, Omri; Skalko-Basnet, Natasa; Agarwal, Krishna; Ahluwalia, Balpreet Singh (Conference object; Konferansebidrag, 2021)
      Chip-based Evanescent Light Scattering (cELS) utilizes the multiple modes of a high-index contrast optical waveguide for near-field illumination of unlabeled samples, thereby repositioning the highest spatial frequencies of the sample into the far-field. The multiple modes scattering off the sample with different phase differences is engineered to have random spatial distributions within the integration ...

    • Label-free nanoscopy enabled by coherent imaging with photonic waveguides 

      Ströhl, Florian; Opstad, Ida Sundvor; Tinguely, Jean-Claude; Dullo, Firehun Tsige; Kaminski, Clemens F.; Ahluwalia, Balpreet Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-07-29)
      In this project it was found that Fourier ptychographic microscopy can be improved far beyond its conventional limits via waveguide-based optical systems. Extensive in silico studies showed that images obtained on highrefractive index material waveguide chips in conjunction with hyperspectral illumination light and finely designed waveguide geometries can be combined via a modified phase-retrieval ...

    • Label-free superior contrast with c-band ultra-violet extinction microscopy 

      Wolfson, Deanna; Opstad, Ida Sundvor; Hansen, Daniel Henry; Mao, Hong; Ahluwalia, Balpreet Singh; Ströhl, Florian (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-03)
      In 1934, Frits Zernike demonstrated that it is possible to exploit the sample’s refractive index to obtain superior contrast images of biological cells. The refractive index contrast of a cell surrounded by media yields a change in the phase and intensity of the transmitted light wave. This change can be due to either scattering or absorption caused by the sample. Most cells are transparent at visible ...

    • A Lagrangian Snow Evolution System for Sea Ice Applications (SnowModel‐LG): Part II - Analyses 

      Stroeve, Julienne C.; Liston, Glen E.; Buzzard, Samantha; Zhou, Lu; Mallett, Robbie; Barrett, Andrew; Tschudi, Mark; Tsamados, Michel; Itkin, Polona; Stewart, Scott (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-02)
      Sea ice thickness is a critical variable, both as a climate indicator and for forecasting sea ice conditions on seasonal and longer time scales. The lack of snow depth and density information is a major source of uncertainty in current thickness retrievals from laser and radar altimetry. In response to this data gap, a new Lagrangian snow evolution model (SnowModel‐LG) was developed to simulate snow ...

    • A Lagrangian Snow‐Evolution System for Sea‐Ice Applications (SnowModel‐LG): Part I – Model Description 

      Liston, Glen E.; Itkin, Polona; Stroeve, Julienne C.; Tschudi, Mark; Stewart, J. Scott; Pedersen, Stine Højlund; Reinking, A.K.; Elder, Kelly (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-06)
      A Lagrangian snow-evolution model (SnowModel-LG) was used to produce daily, pan-Arctic, snow-on-sea-ice, snow property distributions on a 25 × 25-km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective-Analysis for Research and Applications-Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis-5th ...

    • Land cover changes detection in polarimetric SAR data using algebra, similarity and distance based methods 

      Najafi, Amir; Hasanlou, Hasan; Akbari, Vahid (Journal article; Tidsskriftartikkel, 2017-09-27)
      Monitoring and surveillance changes around the world need powerful methods, so detection, visualization, and assessment of significant changes are essential for planning and management. Incorporating polarimetric SAR images due to interactions between electromagnetic waves and target and because of the high spatial resolution almost one meter can be used to study changes in the Earth's surface. Full ...

    • Large amplitude blob propagation in the SOL of Alcator C-Mod and comparison to theoretical model 

      Kube, Ralph; Garcia, Odd Erik; LaBombard, Brian; Terry, James L.; Zweben, Stewart (Conference object; Konferansebidrag, 2012)

    • Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning 

      Bianchi, Filippo Maria; Espeseth, Martine; Borch, Njål Trygve (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-14)
      We propose a deep-learning framework to detect and categorize oil spills in synthetic aperture radar (SAR) images at a large scale. Through a carefully designed neural network model for image segmentation trained on an extensive dataset, we obtain state-of-the-art performance in oil spill detection, achieving results that are comparable to results produced by human operators. We also introduce a ...

    • Large-Scale Mapping of Small Roads in Lidar Images Using Deep Convolutional Neural Networks 

      Salberg, Arnt Børre; Trier, Øivind Due; Kampffmeyer, Michael C. (Chapter; Bokkapittel, 2017-05-19)
      Detailed and complete mapping of forest roads is important for the forest industry since they are used for timber transport by trucks with long trailers. This paper proposes a new automatic method for large-scale mapping forest roads from airborne laser scanning data. The method is based on a fully convolutional neural network that performs end-to-end segmentation. To train the network, a large set ...

    • Laser-Generated Scholte Waves in Floating Microparticles 

      Ranjan, Abhishek; Ahmad, Azeem; Ahluwalia, Balpreet Singh; Melandsø, Frank (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-04)
      This study aims to demonstrate the generation and detection of Scholte waves inside polystyrene microparticles. This was proven using both experimental analysis and COMSOL simulation. Microspheres of different sizes were excited optically with a pulsed laser (532 nm), and the acoustic signals were detected using a transducer (40 MHz). On analyzing the laser-generated ultrasound signals, the results ...

    • Late summer sea ice segmentation with multi-polarisation SAR features in C- and X-band 

      Fors, Ane Schwenke; Brekke, Camilla; Doulgeris, Anthony Paul; Eltoft, Torbjørn; Renner, Angelika; Gerland, Sebastian (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-09-01)
      In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg- fast first-year and old sea ice during a week with air temperatures varying around zero degrees Celsius. In situ data consisting of sea ice ...

    • Learning latent representations of bank customers with the Variational Autoencoder 

      Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-15)
      Learning data representations that reflect the customers’ creditworthiness can improve marketing campaigns, customer relationship management, data and process management or the credit risk assessment in retail banks. In this research, we show that it is possible to steer data representations in the latent space of the Variational Autoencoder (VAE) using a semi-supervised learning framework and a ...

    • Learning Nanoscale Motion Patterns of Vesicles in Living Cells 

      Sekh, Arif Ahmed; Opstad, Ida Sundvor; Birgisdottir, Åsa B.; Myrmel, Truls; Ahluwalia, Balpreet Singh; Agarwal, Krishna; Prasad, Dilip K. (Conference object; Konferansebidrag, 2020-08-05)
      Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution (~250 nm), inside living biological cells is a challenging problem. State-of-the-art CV approaches based on detection, tracking, optical flow or deep learning perform poorly for this problem. We propose an integrative approach, built upon physics based simulations, nanoscopy algorithms, and shallow ...