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Introduction: Rates of delivery by cesarean section have gradually risen in many parts of the world, and it is regarded as a safe surgical procedure with expanded indications. We assessed maternal complications within 6 weeks postpartum after planned cesarean section and after planned vaginal delivery among patients without medical indication for cesarean section. Material and methods: This was a
This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from repetitions of rigidly-transformed coplanar local features. The proposed solvers incorporate lens distortion into the camera model and extend accurate rectification to wide-angle images that contain nearly any type of coplanar repeated content. We demonstrate a principled approach to
Speaker localization using microphone arrays depends on accurate time delay estimation techniques. For decades, methods based on the generalized cross correlation with phase transform (GCC-PHAT) have been widely adopted for this purpose. Recently, the GCC-PHAT has also been used to provide input features to neural networks in order to remove the effects of noise and reverberation, but at the cost
While prenatal exposure to ambient air pollution has been shown to be associated with reduced birth weight, there is substantial heterogeneity across studies, and few epidemiological studies have utilized source-specific exposure data. The aim of the present study was, therefore, to investigate the associations between local, source-specific exposure to fine particulate matter (PM2.5) during pregn
Regulations restrict UAVs to fly only within direct view of the pilot, limiting their ability to support critical societal functions. One potential way to move beyond this limitation is by placing a 360-degree camera on the vehicle and using its feed to provide operators with a view that is the equivalent to being on the vehicle. This necessitates a cockpit user interface (UI) that amongst other t
Today, the advances in airborne LIDAR technology provide high-resolution datasets that allow specialists to detect archaeological features hidden under wooded areas more efficiently. Still, the complexity and large scale of these datasets require automated analysis. In this respect, artificial intelligence (AI)-based analysis has recently created an alternative approach for interpreting remote sen
The filtered backprojection (FBP) algorithm is viewed as a preferred candidate for general bistatic synthetic aperture radar (BiSAR) imaging since it does not pose any restrictions on SAR configurations or flight paths. However, high-efficient autofocus methods such as phase gradient autofocus (PGA) or Mapdrift (MD) cannot be effectively integrated with the FBP algorithm due to the unknown propert
Most 3d human pose estimation methods assume that input – be it images of a scene collected from one or several viewpoints, or from a video – is given. Consequently, they focus on estimates leveraging prior knowledge and measurement by fusing information spatially and/or temporally, whenever available. In this paper we address the problem of an active observer with freedom to move and explore the
Existing state-of-the-art estimation systems can detect 2d poses of multiple people in images quite reliably. In contrast, 3d pose estimation from a single image is ill-posed due to occlusion and depth ambiguities. Assuming access to multiple cameras, or given an active system able to position itself to observe the scene from multiple viewpoints, reconstructing 3d pose from 2d measurements becomes
Many people and organizations across the globe work towards a sustainable future. Artificial intelligence (AI) can be a powerful tool in their efforts.AI technologies, which aim to imitate the natural intelligence of humans and animals, have made enormous progress in the past decade. AI has brought us a whole range of futuristic tools — from self-driving cars to virtual assistants, smart home appl
The brain systems of episodic memory and oculomotor control are tightly linked, suggesting a crucial role of eye movements in memory. But little is known about the neural mechanisms of memory formation across eye movements in unrestricted viewing behavior. Here, we leverage simultaneous eye tracking and EEG recording to examine episodic memory formation in free viewing. Participants memorized mult
This paper discusses a Python interface for the recently published Dune-Fem-DG module which provides highly efficient implementations of the discontinuous Galerkin (DG) method for solving a wide range of nonlinear partial differential equations (PDEs). Although the C++ interfaces of Dune-Fem-DG are highly flexible and customizable, a solid knowledge of C++ is necessary to make use of this powerful
Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shi
Describing long-ranged electrostatics using short-ranged pair potentials is appealing because the computational complexity scales linearly with the number of particles. The foundation of the approach presented here is to mimic the long-ranged medium response by cancelling electric multipoles within a small cutoff sphere. We propose a rigorous and formally exact new method that cancels up to infini
Hypothesis: The stability of colloidal dispersions in the presence of multivalent ions depends strongly on the electrostatic interactions between the suspended particles. Of particular interest are colloidal particles having dimensions in the nanometric range and with an anisotropic shape due to its high surface area per unit mass, for example clay, which has the key characteristic of a negatively
Low rank structures are present in many applications of computer vision and machine learning. A popular approach consists of explicitly parameterising the set or matrices with sought rank, leading to a bilinear factorisation, reducing the problem to find the bilinear factors. While such an approach can be efficiently implemented using second-order methods, such as Levenberg-Marquardt (LM) or Varia
BACKGROUND: Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and clinical status on admission are strongly associated with outcome after out-of-hospital cardiac arrest (OHCA). Early prediction of outcome may inform prognosis, tailor therapy and help in interpreting the intervention effect in heterogenous clinical trials. This study aimed to create a model for early predict
