Viser treff 101-120 av 947

    • KAIRA Science Results 

      McKay, Derek (Conference object; Konferansebidrag, 2018)
    • 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 ...
    • Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy 

      Wickstrøm, Kristoffer; Løkse, Sigurd Eivindson; Kampffmeyer, Michael; Yu, Shujian; Príncipe, José C.; Jenssen, Robert (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-03)
      The aquaculture industry is expanding to meet the daily requirements of humanity from high-quality seafood. In this regard, intensive aquaculture systems are suggested, resulting in high production but being challenged with immunosuppression and disease invaders. Antibiotics were used for a long time to protect and treat aquatic animals; however, continuous use led to severe food safety issues, ...
    • Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks 

      Choi, Changkyu; Kampffmeyer, Michael; Jenssen, Robert (Conference object; Konferansebidrag, 2020)
      Data without annotation are easy to obtain in the real-world, however, established supervised learning methods are not applicable to analyze them. Several learning approaches have been proposed in recent years to exploit the underlying structure of the data without requiring annotations. Semi-supervised learning aims to improve the predictive performance of these unsupervised approaches, by exploiting ...
    • Uptake and Degradation of Bacteriophages by Liver Sinusoidal Endothelial Cells 

      Wolfson, Deanna; Øie, Cristina Ionica; Yasunori, Tanji; Dumitriu, Gianina; McCourt, Peter Anthony; Sørensen, Karen Kristine; Smedsrød, Bård; Ahluwalia, Balpreet Singh (Conference object; Konferansebidrag, 2018)
      <p>Bacteriophages (briefly, “phages”) are viruses which target bacteria, and are non-infectious to eukaryotic cells. It is estimated that more than 30 billion phages cross into the human body from the gut each day1, and eventually need to be cleared from the blood circulation. The liver plays a central role in pathogen clearance, and liver sinusoidal endothelial cells (LSECs), which form the lining ...
    • Polarimetric Guided Nonlocal Means Covariance Matrix Estimation for Defoliation Mapping 

      Agersborg, Jørgen Andreas; Anfinsen, Stian Normann; Jepsen, Jane Uhd (Conference object; Konferansebidrag, 2020)
      In this study we investigate the potential for using synthetic aperture radar (SAR) data to provide high resolution defoliation and regrowth mapping of trees in the tundra-forest ecotone. Using aerial photographs, four areas with live forest and four areas with dead trees were identified. Quad-polarimetric SAR data from RADARSAT-2 was collected from the same area, and the complex multilook polarimetric ...
    • Generation of Lidar-Predicted Forest Biomass Maps from Radar Backscatter with Conditional Generative Adversarial Networks 

      Björk, Sara; Anfinsen, Stian Normann; Næsset, Erik; Gobakken, Terje; Zahabu, Eliakimu (Conference object; Konferansebidrag, 2020)
    • Heterogeneous Change Detection with Self-supervised Deep Canonically Correlated Autoencoders 

      Figari Tomenotti, Federico; Luppino, Luigi Tommaso; Hansen, Mads Adrian; Moser, Gabriele; Anfinsen, Stian Normann (Conference object; Konferansebidrag, 2020)
    • Change Detection with Heterogeneous Remote Sensing Data: From Semi-Parametric Regression to Deep Learning 

      Moser, Gabriele; Anfinsen, Stian Normann; Luppino, Luigi Tommaso; Serpico, Sebastian Bruno (Conference object; Konferansebidrag, 2020)
    • Image denoising in acoustic microscopy using block-matching and 4D filter 

      Gupta, Shubham Kumar; Pal, Rishant; Ahmad, Azeem; Melandsø, Frank; Habib, Anowarul (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-14)
      Scanning acoustic microscopy (SAM) is a label-free imaging technique used in biomedical imaging, non-destructive testing, and material research to visualize surface and sub-surface structures. In ultrasonic imaging, noises in images can reduce contrast, edge and texture details, and resolution, negatively impacting post-processing algorithms. To reduce the noises in the scanned image, we have employed ...
    • Better synoptic and subseasonal sea ice thickness predictions are urgently required: a lesson learned from the YOPP data validation 

      Yang, Qinghua; Xiu, Yongwu; Luo, Hao; Wang, Jinfei; Landy, Jack Christopher; Bushuk, Mitchell; Wang, Yiguo; Liu, Jiping; Chen, Dake (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-20)
      In the context of global warming, Arctic sea ice has declined substantially during the satellite era (Kwok 2018). The retreating and thinning of Arctic sea ice provide opportunities for human activities in the Arctic, such as tourism, fisheries, shipping, natural resource exploitation, and wildlife management; however, new risks emerge. To ensure the safety and emergency management of human activities ...
    • Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice 

      Nandan, Vishnu; Willatt, Rosemary; Mallett, Robbie; Stroeve, Julienne; Geldsetzer, Torsten; Scharien, Randall; Tonboe, Rasmus; Yackel, John; Landy, Jack Christopher; Clemens-Sewall, David; Jutila, Arttu; Wagner, David N.; Krampe, Daniela; Huntemann, Marcus; Mahmud, Mallik; Jensen, David; Newman, Thomas; Hendricks, Stefan; Spreen, Gunnar; Macfarlane, Amy; Schneebeli, Martin; Mead, James; Ricker, Robert; Gallagher, Michael; Duguay, Claude; Raphael, Ian; Polashenski, Chris; Tsamados, Michel; Matero, Ilkka; Hoppmann, Mario (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-02)
      Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. ...
    • Attention-guided Temporal Convolutional Network for Non-intrusive Load Monitoring 

      Ren, Huamin; Su, Xiaomeng; Jenssen, Robert; Li, Jingyue; Anfinsen, Stian Normann (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-01)
      With the prevalence of smart meter infrastructure, data analysis on consumer side becomes more and more important in smart grid systems. One of the fundamental tasks is to disaggregate users' total consumption into appliance-wise values. It has been well noted that encoding of temporal dependency is a key issue for successful modelling of the relations between the total consumption and its decomposed ...
    • Universality of intermittent fluctuations in the Alcator C-Mod scrape-off layer 

      Kube, Ralph; Garcia, Odd Erik; Theodorsen, Audun; Brunner, Dan; Kuang, Adam; LaBombard, Brian; Terry, Jim L. (Conference object; Konferansebidrag, 2017)
    • Blob shapes in the scrape-off layer: Comparison of measurements to simulations 

      Kube, Ralph; Garcia, Odd Erik; Theodorsen, Audun; Brunner, Dan; Kuang, Adam; LaBombard, Brian; Terry, Jim L. (Conference object; Konferansebidrag, 2017)
    • Adhesive free PVDF copolymer focused transducers for high frequency acoustic imaging 

      Habib, Anowarul; Wagle, Sanat; Melandsø, Frank (Conference object; Konferansebidrag, 2019)
      The present study has demonstrated to produce a reliable PVDF copolymer focused transducers from a layer-by-layer deposition method by engraving milled spherical cavies in a PEI polymer substrate. The proposed method which process P(VDF-TrFE) from the fluid phase, is adhesive-free in the sense that it does not require any additional adhesive layers for material binding. The transducer was acoustically ...
    • Dust Trajectory Calculations in the Inner Heliosphere and Circumstellar Debris Disks 

      Mann, Ingrid; Stamm, Johann Immanuel; Czechowski, Andrzej; Baumann, Carsten; Myrvang, Margaretha; Li, Aigen (Conference object; Konferansebidrag, 2018)
    • Subseasonal Predictions of Polar Low Activity Using a Hybrid Statistical-Dynamical Approach 

      Boyd, Kevin; Wang, Zhuo; Walsh, John; Stoll, Johannes Patrick (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-21)
      The subseasonal prediction of polar low (PL) activity is explored using a hybrid statistical-dynamical approach. A previously developed PL genesis potential index is paired with ECMWF reforecasts and forecasts to predict regional statistics of PL activity across the sub-Arctic. Regional PL activity is skillfully predicted in all regions at forecast ranges of up to a month. Additionally, the ...
    • 21st Century Scenario Forcing Increases More for CMIP6 Than CMIP5 Models 

      Fredriksen, Hege-Beate; Smith, Christopher J.; Modak, Angshuman; Rugenstein, Maria (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-16)
      Although the Coupled Model Intercomparison Project 6 (CMIP6) protocol provides an experiment to estimate effective radiative forcing (ERF), it is only quantified for few models. We present new estimates of ERF for models participating in CMIP6 by applying the method developed in Fredriksen et al. (2021, https://doi.org/10.1029/2020JD034145), and validate our approach with available fixed-SST forcing ...
    • Improving sea surface temperature in a regional ocean model through refined sea surface temperature assimilation 

      Iversen, Silje Christine; Sperrevik, Ann Kristin; Goux, Olivier (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-26)
      Infrared (IR) and passive microwave (PMW) satellite sea surface temperature (SST) retrievals are valuable to assimilate into high-resolution regional ocean forecast models. Still, there are issues related to these SSTs that need to be addressed to achieve improved ocean forecasts. Firstly, satellite SST products tend to be biased. Assimilating SSTs from different providers can thus cause the ocean ...