Credit scoring models based on accepted applications may be biased and their consequences can have a statistical and economic impact. Reject inference is the process of attempting to infer the creditworthiness status of the rejected applications. Inspired by the promising results of semi-supervised deep generative models, this research develops two novel Bayesian models for reject inference in credit ...

Autoencoders learn data representations (codes) in such a way that the input is reproduced at the output of the network. However, it is not always clear what kind of properties of the input data need to be captured by the codes. Kernel machines have experienced great success by operating via inner-products in a theoretically well-defined reproducing kernel Hilbert space, hence capturing topological ...

The implementation of piezoelectric sensors is degraded due to surface defects, delamination, and extreme weathering conditions, to mention a few. Hence, the sensor needs to be diagnosed before the efficacious implementation in the structural health monitoring (SHM) framework. To rescue the problem, a novel experimental method based on Coulomb coupling is utilised to visualise the evolution of ...

We present a deep-learning-based algorithm to jointly solve a reconstruction problem and a wavefront set extraction problem in tomographic imaging. The algorithm is based on a recently developed digital wavefront set extractor as well as the well-known microlocal canonical relation for the Radon transform. We use the wavefront set information about x-ray data to improve the reconstruction ...

Multi-frequency echosounder data can provide a broad understanding of the underwater environment in a non-invasive manner. The analysis of echosounder data is, hence, a topic of great importance for the marine ecosystem. Semantic segmentation, a deep learning based analysis method predicting the class attribute of each acoustic intensity, has recently been in the spotlight of the fisheries and aquatic ...

Prosjektets mål er å bidra til økt kunnskap om hvordan etablere delt situasjonsforståelse mellom sentrale aktører innen SAR i Nordområdet. Prosjektgruppa har arbeidet ut ifra en menneske-teknologi-organisasjon (MTO) tilnærming og hvor vi har sett på <br>1) menneskelige og organisatoriske faktorer og <br>2) tekniske faktorer som virker inn på etableringen av delt situasjonsforståelse mellom aktører.<br> ...

Dynamic speckle illumination (DSI) has recently attracted strong attention in the feld of biomedical imaging as it pushes the limits of interference microscopy (IM) in terms of phase sensitivity, and spatial and temporal resolution compared to conventional light source illumination. To date, despite conspicuous advantages, it has not been extensively implemented in the feld of phase imaging due ...

This study analyses the departure of the velocity-variances profiles from their quasi-steady state described by the mixed-layer similarity, using large-eddy simulations with different prescribed shapes and time scales of the surface kinematic heat flux decay. Within the descriptive frames where the time is tracked solely by the forcing time scale (either constant or time-dependent) describing the ...

Contrast in fluorescence microscopy images allows for the differentiation between different structures by their difference in intensities. However, factors such as point-spread function and noise may reduce it, affecting its interpretability. We identified that fluctuation of emitters in a stack of images can be exploited to achieve increased contrast when compared to the average and Richardson-Lucy ...

Unscheduled power disturbances cause severe consequences for customers and grid operators. To avoid suchevents, it is important to identify the causes and localize the sources of the disturbances in the power distribution network. In this work, we focus on a specific power grid in the Arctic region of Northern Norway that experiences an increased frequency of failures of unspecified origin.