Sökresultat

The training of the state-of-the-art Deep Neural Networks (DNNs) consumes massive amounts of energy, while the human brain learns new tasks with remarkable efficiency. Currently, the training of DNNs relies almost exclusively on Backpropagation (BP). However, BP faces criticism due to its biologically implausible nature, underscoring the significant disparity in performance and energy efficiency b

Understanding metabolic processes of soil fungi is essential for elucidating their ecological roles in biogeochemical cycles and responses to emergent environmental stressors. Here, we demonstrate the potential of using stable isotope probing Raman (SIP-Raman) microspectroscopy in microfluidics technology-based soil chips to trace glucose metabolism rates and stress responses in laboratory grown f

This study critically explores the launch of the mission for 100 climate neutral cities in Europe. Key elements of the mission are introduced and analysed along with some of its challenges and ambiguities.

The islet β cells are the specific targets in an autoimmune process that eventually leads to the clinical onset of type 1 diabetes (T1D). The etiology is related to human leukocyte antigen (HLA) DR-DQ genetic factors that are necessary but not sufficient for disease development. The environmental etiology is related to enterovirus infection in early childhood resulting in two endotypes. In HLA DR4

ObjectivesTo compare head acceleration between blind football players and non-disabled football players, and between anticipated and unanticipated conditions in blind football players.DesignLaboratory-based exploratory study.MethodsParticipants were ten football players (five blind football, five non-disabled; 80% female). Standardized head perturbations were applied in flexion, extension, lateral

This study investigates the first Climate City Contracts (CCCs) in Sweden and consequently Europe. To do so, it evaluates the content of the Swedish CCCs against a framework for best practice deep decarbonisation plans.

This study explores the global trend of cities declaring a climate emergency. To do so, it delves into the experiences in Sweden with climate emergency statements and if or how cities are adopting a ”climate emergency mode”.

A synchrotron-based experiment was carried out to demonstrate the potential of x-ray photon correlation spectroscopy (XPCS) to characterize collective dynamics driven by superparamagnetic iron oxide nanoparticles (SPIONs) during magnetomotive ultrasound (MMUS) imaging. MMUS is a developing diagnostic imaging technique that has the potential to enable more precise cancer staging than other clinical

Drought-induced canopy browning and recovery dynamics threaten ecosystem stability worldwide, with Australia serving as a representative case. This study examined the 2019–2020 drought and subsequent recovery in Eucalyptus forests across two bioregions of the Australian state of New South Wales (NSW): the North Coast and South Eastern Highlands. Canopy browning and recovery were quantified using a

Stickler syndrome is a collection of hereditary conditions that impact connective tissue, mainly collagen, and can cause a variety of symptoms, such as joint and bone abnormalities, hearing loss, and visual impairments. Previous studies suggest that mutations in the collagen-encoding genes are a primary cause of SS. These mutations can be inherited from parents to offspring and may vary significan

Lines and points are complementary local features, whose combination has proven effective for applications such as SLAM and Structure-from-Motion. The backbone of these pipelines are the local feature matchers, establishing correspondences across images. Traditionally, point and line matching have been treated as independent tasks. Recently, GlueStick proposed a GNN-based network that simultane-ou

The ability to interpret and comprehend a 3D scene is essential for many vision and robotics systems. In numerous applications, this involves 3D object detection, i.e. identifying the location and dimensions of objects belonging to a specific category, typically represented as bounding boxes. This has traditionally been solved by training to detect a fixed set of categories, which limits its use.

Monocular depth estimation (MDE) models have undergone significant advancements over recent years. Many MDE models aim to predict affine-invariant relative depth from monocular images, while recent developments in large-scale training and vision foundation models enable reasonable estimation of metric (absolute) depth. However, effectively leveraging these predictions for geometric vision tasks, i

Line segments are powerful features complementary to points. They offer structural cues, robust to drastic viewpoint and illumination changes, and can be present even in texture-less areas. However, describing and matching them is more challenging compared to points due to partial occlusions, lack of texture, or repetitiveness. This paper introduces a new matching paradigm, where points, lines, an

In this paper we introduce the Tangent Sampson error, which is a generalization of the classical Sampson error in two-view geometry that allows for arbitrary central camera models. It only requires local gradients of the distortion map at the original correspondences (allowing for pre-computation) resulting in a negligible increase in computational cost when used in RANSAC or local refinement. The

In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to offering strong geometric cues, they are also omnipresent in urban landscapes and indoor scenes. Despite their apparent advantages, current line-based reconstruction methods are far behind their point-based counterparts.