Viser treff 361-380 av 1276

    • OpenMetBuoy-v2021: An Easy-to-Build, Affordable, Customizable, Open-Source Instrument for Oceanographic Measurements of Drift and Waves in Sea Ice and the Open Ocean 

      Rabault, Jean; Nose, Takehiko; Hope, Gaute; Müller, Malte; Breivik, Øyvind; Voermans, Joey; Hole, Lars Robert; Bohlinger, Patrik; Waseda, Takuji; Kodaira, Tsubasa; Katsuno, Tomotaka; Johnson, Mark; Sutherland, Graig; Johansson, Anna Malin Kristin; Christensen, Kai Haakon; Garbo, Adam; Jensen, Atle; Gundersen, Olav; Marchenko, Aleksey; Babanin, Alexander (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-02-26)
      There is a wide consensus within the polar science, meteorology, and oceanography communities that more in situ observations of the ocean, atmosphere, and sea ice are required to further improve operational forecasting model skills. Traditionally, the volume of such measurements has been limited by the high cost of commercially available instruments. An increasingly attractive solution to this ...
    • Clinically relevant features for predicting the severity of surgical site infections 

      Boubekki, Ahcene; Myhre, Jonas Nordhaug; Luppino, Luigi Tommaso; Mikalsen, Karl Øyvind; Revhaug, Arthur; Jenssen, Robert (Journal article; Tidsskriftartikkel, 2021)
      Surgical site infections are hospital-acquired infections resulting in severe risk for patients and significantly increased costs for healthcare providers. In this work, we show how to leverage irregularly sampled preoperative blood tests to predict, on the day of surgery, a future surgical site infection and its severity. Our dataset is extracted from the electronic health records of patients who ...
    • Two-dimensional CNN-based distinction of human emotions from EEG channels selected by Multi-Objective evolutionary algorithm 

      Moctezuma, Luis Alfredo; Abe, Takashi; Molinas Cabrera, Maria Marta (Journal article; Tidsskriftartikkel; Peer reviewed, 2022)
      In this study we explore how different levels of emotional intensity (Arousal) and pleasantness (Valence) are reflected in Electroencephalographic (EEG) signals. We performed the experiments on EEG data of 32 subjects from the DEAP public dataset, where the subjects were stimulated using 60-second videos to elicitate different levels of Arousal/Valence and then self-reported the rating from 1-9 ...
    • Inferring the Dielectric Properties of Oil Slick from Multifrequency SAR imagery via a Polarimetric Two-Scale Model 

      Quigley, Cornelius; Brekke, Camilla; Eltoft, Torbjørn (Journal article; Tidsskriftartikkel, 2021-04)
      We apply a polarimetric two-scale model to multifrequency synthetic aperture radar imagery of verified oil slicks measured by DLRs F-SAR instrument, which can acquire high spatial resolution and high signal-to-noise data. The purpose, is to determine the permittivity of the scattering surface via an inversion procedure. The ocean surface is modelled as an ensemble of randomly orientated, tilted ...
    • Reconsidering Representation Alignment for Multi-View Clustering 

      Trosten, Daniel Johansen; Løkse, Sigurd Eivindson; Jenssen, Robert; Kampffmeyer, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-13)
      Aligning distributions of view representations is a core component of today’s state of the art models for deep multi-view clustering. However, we identify several drawbacks with naïvely aligning representation distributions. We demonstrate that these drawbacks both lead to less separable clusters in the representation space, and inhibit the model’s ability to prioritize views. Based on these ...
    • Photonic-chip: a multimodal imaging tool for histopathology 

      Villegas, Luis; Dubey, Vishesh Kumar; Tinguely, Jean-Claude; Coucheron, David Andre; Priyadarshi, Anish; Acuña Maldonado, Sebastian Andres; Agarwal, Krishna; Mateos, Jose M; Nystad, Mona; Hovd, Aud-Malin Karlsson; Fenton, Kristin Andreassen; Ahluwalia, Balpreet Singh (Conference object; Konferansebidrag, 2021-04)
      We propose the photonic-chip as a multimodal imaging platform for histopathological assessment, allowing large fields-of-view across diverse microscopy methods including total internal reflection fluorescence and single-molecule localization.
    • Deep Semisupervised Teacher–Student Model Based on Label Propagation for Sea Ice Classification 

      Khaleghian, Salman; Ullah, Habib; Kræmer, Thomas; Eltoft, Torbjørn; Marinoni, Andrea (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-14)
      In this article, we propose a novelteacher–student-based label propagation deep semisupervised learning (TSLP-SSL) method for sea ice classification based on Sentinel-1 synthetic aperture radar data. For sea ice classification, labeling the data precisely is very time consuming and requires expert knowledge. Our method efficiently learns sea ice characteristics from a limited number of labeled samples ...
    • ExtremeEarth meets satellite data from space 

      Hagos, Desta Haileselassie; Kakantousis, Theofilos; Vlassov, Vladimir; Sheikholeslami, Sina; Wang, Tianze; Dowling, Jim; Paris, Claudia; Marinelli, Daniele; Weikmann, Giulio; Bruzzone, Lorenzo; Khaleghian, Salman; Kræmer, Thomas; Eltoft, Torbjørn; Marinoni, Andrea; Pantazi, Despina-Athanasia; Stamoulis, George; Bilidas, Dimitris; Papadakis, George; Mandilaras, George; Koubarakis, Manolis; Troumpoukis, Antonis; Konstantopoulos, Stasinos; Muerth, Markus; Appel, Florian; Fleming, Andrew; Cziferszky, Andreas (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-08-26)
      Bringing together a number of cutting-edge technologies that range from storing extremely large volumes of data all the way to developing scalable machine learning and deep learning algorithms in a distributed manner and having them operate over the same infrastructure poses unprecedented challenges. One of these challenges is the integration of European Space Agency (ESA)’s Thematic Exploitation ...
    • Results of the Dragon 4 Project on New Ocean Remote Sensing Data for Operational Applications 

      Gibert, Ferran; Boutin, Jacqueline; Dierking, Wolfgang Fritz Otto; Granados, Alba; Li, Yan; Makhoul, Eduard; Meng, Junmin; Supply, Alexandre; Vendrell, Ester; Vergely, Jean-Luc; Wang, Jin; Yang, Jungang; Xiang, Kunsheng; Yin, Xiaobin; Zhang, Xi (Journal article; Tidsskriftsartikkel, 2021-07-20)
      This paper provides an overview of the Dragon 4 project dealing with operational monitoring of sea ice and sea surface salinity (SSS) and new product developments for altimetry data. To improve sea ice thickness retrieval, a new method was developed to match the Cryosat-2 radar waveform. Additionally, an automated sea ice drift detection scheme was developed and tested on Sentinel-1 data, and the ...
    • The influence of surface charge on the coalescence of ice and dust particles in the mesosphere and lower thermosphere 

      Baptiste, Joshua; Williamson, Connor; Fox, John; Stace, Anthony J.; Hassan, Muhammad; Braun, Stefanie; Stamm, Benjamin; Mann, Ingrid; Besley, Elena (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-09)
      Agglomeration of charged ice and dust particles in the mesosphere and lower thermosphere is studied using a classical electrostatic approach, which is extended to capture the induced polarisation of surface charge. Collision outcomes are predicted whilst varying the particle size, charge, dielectric constant, relative kinetic energy, collision geometry and the coefficient of restitution. In ...
    • IA-SSLM: Irregularity-Aware Semi-Supervised Deep Learning Model for Analyzing Unusual Events in Crowds 

      Aljaloud, Abdulaziz Salamah; Ullah, Habib (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-17)
      Analyzing unusual events is significantly important for video surveillance to ensure people safety. These events are characterized by irregular patterns that do not conform to the expected behavior in the surveillance scenes. We present a novel irregularity-aware semi-supervised deep learning model (IA-SSLM) for detection of unusual events. While most existing works depend on the availability ...
    • Conditions for Topside Ion Line Enhancements 

      Rexer, Theresa; Leyser, Thomas; Gustavsson, Björn Johan; Rietveld, Michael T. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-17)
      Enhanced ion line spectra as a response to magnetic field-aligned high frequency (HF) pumping of the overdense polar ionosphere with left-handed circular polarization, can be observed at the top and bottomside F-region ionosphere under certain conditions. The European Incoherent Scatter (EISCAT) UHF radar was directed in magnetic zenith on October 18th and 19th, 2017 while stepping the pump ...
    • A transparent waveguide chip for versatile total internal reflection fluorescence-based microscopy and nanoscopy 

      Priyadarshi, Anish; Wolfson, Deanna; Ahmad, Azeem; Jayakumar, Nikhil; Dubey, Vishesh Kumar; Tinguely, Jean-Claude; Ahluwalia, Balpreet Singh; Murugan, Ganapathy Senthil (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-08-20)
      Total internal reflection fluorescence (TIRF) microscopy is an imaging technique that, in comparison to confocal microscopy, does not require a trade-off between resolution, speed, and photodamage. Here, we introduce a waveguide platform for chip-based TIRF imaging based on a transparent substrate, which is fully compatible with sample handling and imaging procedures commonly used with a standard ...
    • Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks 

      Geist, Moritz; Petersen, Philipp; Raslan, Mones; Schneider, Reinhold; Kutyniok, Gitta Astrid Hildegard (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-05)
      We perform a comprehensive numerical study of the effect of approximation-theoretical results for neural networks on practical learning problems in the context of numerical analysis. As the underlying model, we study the machine-learning-based solution of parametric partial differential equations. Here, approximation theory for fully-connected neural networks predicts that the performance of the ...
    • Quantification of the NA dependent change of shape in the image formation of a z-polarised fluorescent molecule using vectorial diffraction simulations 

      Ströhl, Florian; Bruggeman, Ezra; Rowlands, Christopher; Wolfson, Deanna; Ahluwalia, Balpreet Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-19)
      The point spread function of a fixed fluorophore with its dipole axis colinear to the optical axis appears donut-shaped when seen through a microscope, and its light distribution in the pupil plane is radially polarized. Yet other techniques, such as photolithography, report that this same light distribution in the pupil plane appears as a solid spot. How can this same distribution lead to a spot ...
    • Estimating Radiative Forcing With a Nonconstant Feedback Parameter and Linear Response 

      Fredriksen, Hege-Beate; Rugenstein, Maria A.A.; Graversen, Rune (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-06)
      A new algorithm is proposed for estimating time-evolving global forcing in climate models. The method is a further development of the work of Forster et al. (2013), <a href=https://doi.org/10.1002/jgrd.50174>https://doi.org/10.1002/jgrd.50174</a>, taking into account the non-constancy of the global feedbacks. We assume that the non-constancy of this global feedback can be explained as a time-scale ...
    • Hydration dynamics and the future of small-amplitude afm imaging in air 

      Santos Hernandez, Sergio; Olukan, Tuza Adeyemi; Lai, Chia-Yun; Chiesa, Matteo (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-23)
      Here, we discuss the effects that the dynamics of the hydration layer and other variables, such as the tip radius, have on the availability of imaging regimes in dynamic AFM—including multifrequency AFM. Since small amplitudes are required for high-resolution imaging, we focus on these cases. It is possible to fully immerse a sharp tip under the hydration layer and image with amplitudes similar to ...
    • Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework 

      Hashemi, Ali; Cai, Chang; Kutyniok, Gitta Astrid Hildegard; Müller, Klaus R.; Nagarajan, Srikantan S.; Haufe, Stefan (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-10-01)
      Methods for electro- or magnetoencephalography (EEG/MEG) based brain source imaging (BSI) using sparse Bayesian learning (SBL) have been demonstrated to achieve excellent performance in situations with low numbers of distinct active sources, such as event-related designs. This paper extends the theory and practice of SBL in three important ways. First, we reformulate three existing SBL algorithms ...
    • Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations 

      Von Albedyll, Luisa; Haas, Christian; Dierking, Wolfgang Fritz Otto (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-04)
      An unusual, large, latent-heat polynya opened and then closed by freezing and convergence north of Greenland’s coast in late winter 2018. The closing presented a natural but well-constrained full-scale ice deformation experiment. We observed the closing of and deformation within the polynya with satellite synthetic-aperture radar (SAR) imagery and measured the accumulated effects of dynamic ...
    • Joint optimization of an autoencoder for clustering and embedding 

      Boubekki, Ahcene; Kampffmeyer, Michael; Brefeld, Ulf; Jenssen, Robert (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-21)
      Deep embedded clustering has become a dominating approach to unsupervised categorization of objects with deep neural networks. The optimization of the most popular methods alternates between the training of a deep autoencoder and a k-means clustering of the autoencoder’s embedding. The diachronic setting, however, prevents the former to beneft from valuable information acquired by the latter. In ...