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Edge detection is an important process in human visual processing. However, as far as we know, few attempts have been made to map the temporal edge detection filters in human vision. To that end, we devised a user study and collected data from which we derived estimates of human temporal edge detection filters based on three different models, including the derivative of the infinite symmetric expo
A method, system and apparatus are disclosed. A network node in communication with a wireless device in a first cell is provided. The network node is configured to receive, from the wireless device, a measurement report associated with the first cell. The network node is further configured to estimate at least one radio resource management, RRM, metric for the first cell and at least one second ce
A method, system and apparatus are disclosed. At least one embodiment includes a wireless device, WD, configured to communicate with a network node, the WD is configured to, and/or includes a radio interface and/or processing circuitry configured to receive a radio resource management, RRM, report configuration. The wireless device is further configured to estimate at least one RRM metric for each
• We aimed to capture possible insights from an AI diagnosing without human guidance.• We believe the result mainly aligns with previous knowledge. Though, vital signs and sex did not aid the AI diagnostics.
The seasonal migrations of insects involve a substantial displacement of biomass with significant ecological and economic consequences for regions of departure and arrival. Remote sensors have played a pivotal role in revealing the magnitude and general direction of bioflows above 150 m. Nevertheless, the take-off and descent activity of insects below this height is poorly understood. Our lidar ob
This paper presents a neural network based semantic plane detection method utilizing polygon representations. The method can for example be used to solve room layout estimations tasks and is built on, combines and further develops several different modules from previous research. The network takes an RGB image and estimates a wireframe as well as a feature space using an hourglass backbone. From t
Background Dyspnoea is one of the emergency department’s (ED) most common and deadly chief complaints, but frequently misdiagnosed and mistreated. We aimed to design a diagnostic decision support which classifies dyspnoeic ED visits into acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), pneumonia and “other diagnoses” by using deep learning and complete, uns
Purpose: Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning. Methods: 546 patients (67% men) undergoing stress 99mTc-tetrofosmin MPI in a CZT camera in the upright and supine position were included (1092 MPIs). Patients were divided into two groups: ICA group included 271 patients who performed an ICA within 6 months of MPI and a control g
We have used a continuous-wave bi-static lidar system based on the Scheimpflug principle in measurements on flying insects above, and in the vicinity of, a small lake located in a forested area in Southern Sweden. The system, which operates on triangulation principles, has a high spatial resolution at close distance, followed by a subsequent decline in resolution further from the sensor, related t
The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, trauma, and COVID-19 include more than 150,000 blood samples and descriptions of critically ill patients. These assets provide a unique opportunity to research and improve the care of the most seriously ill patients through biomarker analyses, proteomic studies, and genetic and epigenetic studies us
Pentachlorophenol (PCP) is a commonly found recalcitrant and toxic groundwater contaminant that resists degradation, bioaccumulates, and has a potential for long-range environmental transport. Taking proper actions to deal with the pollutant accounting for the life cycle consequences requires a better understanding of its behavior in the subsurface. We recognize the huge potential for enhancing de
In this paper, we present a novel algorithmic and hardware co-design approach specifically tailored for efficient 2D convolution implementations, a crucial operation in convolutional neural networks (CNNs). Our method addresses the limitations of existing software-based solutions and hardware-based architectures, delivering significant improvements in asymptotic behavior for generic convolution ca
https://www.svet.lu.se/kajsa-hansson - 2025-12-19
OBJECTIVES: To reach agreement among experts on visual assessments of postural orientation errors (POEs) during the single-leg squat (SLS), and to use expert agreement assessments as ground truth for machine learning (ML) models to evaluate their ability to classify POEs.DESIGN: Methodological study with mixed-methods design.METHODS: POEs of the lower extremity and trunk were assessed from videos
Objectives: To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active surveillance (AS). Patients and methods: A total of 180 patients in the Prostate Cancer Research International Active Surveillance (PRIAS) cohort were prospectively monitored using pre-defined criteria. Diagnostic and re-biopsy slides from 2011 to 2020 (n
In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to assess the strength of neural speech tracking. This enables effective discrimination between attended an
The recently developed Phase-Scaled Reassignment (PSR) can estimate phase-difference between two oscillating transient signals with high accuracy. However, in low signal-to-noise ratios (SNRs) the performance of commonly applied reassignment techniques is known to deteriorate. In order to reduce variance in low SNR, we propose a multitaper PSR (mtPSR) method for phase-difference estimation between
Coherence is a useful measure in many engineering applications. Here, we focus on the case where the input signal to a linear system can be measured free from noise, but the output signal is perturbed by noise. A novel expression for the expectation of a multitaper magnitude squared coherence estimate for this case is presented and verified through numerical evaluation. Additionally, the expressio
Time-frequency reassignment, commonly used to analyze time-varying signals, is a post-processing method that sharpens time-frequency representations. However, the reassignment method is sensitive to noise, making it unsuitable for time-frequency analysis when the signal-to-noise ratio is low. To increase the robustness of the reassignment technique, we develop a novel reassigned multitaper spectro
Background: Assessments of arm motor function are usually based on clinical examinations or self-reported rating scales. Wrist-worn accelerometers can be a good complement to measure movement patterns after stroke. Currently there is limited knowledge of how accelerometry correlate to clinically used scales. The purpose of this study was therefore to evaluate the relationship between intermittent
