Robust Method for Real-time, Continuous, 3D Detection of Obstructed Faces in Indoors Environments

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Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

We analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We prese ...

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some counterintuitive prope ...

In this study, we present the deep learning image segmentation model for drone-based grain size analysis of gravel bars called GALET. The objectives are to quantify the performance of the code and to test its applicability in river research and management. ...

Searching indirectly for physics beyond the standard model requires careful investigation of collider data and methodological advances that are the subject of this thesis. In the first part, we develop a multivariate analysis tool to compare data with the ...

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

Building on an analogy to ductile fracture mechanics, we quantify the size of debris particles created during adhesive wear. Earlier work suggested a linear relation between tangential work and wear debris volume, assuming that the debris size is proportio ...

The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments to assess the impact of human activities or climate chan ...

Statistical models of neural activity are integral to modern neuroscience. Recently interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on ne ...

Robust Method for Real-time, Continuous, 3D Detection of Obstructed Faces in Indoors Environments

Chattez avec Graph Search

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Vision-based Flocking in Aerial Robot Swarms

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Is There a Cap on Longevity? A Statistical Review

Space Oddity? A Statistical Formulation of Conjunction Assessment

GALET: A deep learning image segmentation model for drone-based grain size analysis of gravel bars

Advanced Phenomenology for Indirect New Physics Searches

Improving the Training of Compact Neural Networks for Visual Recognition

Breakdown of Reye’s theory in nanoscale wear

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Applying the Multivariate Time-Rescaling Theorem to Neural Population Models