Results 61 to 70 of about 65,475 (209)

Bayesian Optimization of Grayscale Patterns for Layer‐Height Accuracy in Projection Multi‐Photon 3D Printing

open access: yesLaser &Photonics Reviews, EarlyView.
Bayesian optimization combined with in situ quantitative phase imaging enables autonomous correction of layer‐height deviations in projection multi‐photon lithography. By jointly tuning model parameters and grayscale exposure settings, the method achieves more uniform and accurate layers within 300 prints, offering a fast, data‐efficient route to ...
Jason E. Johnson, Xianfan Xu
wiley   +1 more source

Some Properties of Gromov–Hausdorff Distances [PDF]

open access: yesDiscrete & Computational Geometry, 2012
Let \({\mathcal G}\) stand for the class of all compact metric spaces and let \(GH(.,.)\) be the Gromov-Hausdorff distance on it. In this paper, a modified Gromov-Hausdorff distance is introduced as \(\widehat{GH}(X,Y)= (1/2)\max\{\text{infdis}(X\to Y),\text{infdis}(Y\to X)\}\), \(X,Y\in {\mathcal G}\).
openaire   +3 more sources

Clinical Applications of Multimodal Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review

open access: yesOtolaryngology–Head and Neck Surgery, EarlyView.
Abstract Objective Artificial intelligence (AI) has advanced to simultaneously process visual, auditory, and textual inputs, providing users with “multimodal” AI. Given the clinical integration potential of these tools, otolaryngologists must stay informed. This study reviews current literature on applications of multimodal AI in otolaryngology.
Ying Jie Li   +5 more
wiley   +1 more source

An evaluation of performance measures for arterial brain vessel segmentation

open access: yesBMC Medical Imaging, 2021
Background Arterial brain vessel segmentation allows utilising clinically relevant information contained within the cerebral vascular tree. Currently, however, no standardised performance measure is available to evaluate the quality of cerebral vessel ...
Orhun Utku Aydin   +7 more
doaj   +1 more source

The feasibility principle in community ecology

open access: yesOikos, EarlyView.
The structure and function of ecological communities emerge from interactions among populations within specific environmental contexts. Yet we still lack general principles that explain how communities assemble, which patterns we should expect, and when transitions occur across diverse settings.
Serguei Saavedra
wiley   +1 more source

OPTIMIZATION OF THE ALGORITHM FOR DETERMINING THE HAUSDORFF DISTANCE FOR CONVEX POLYGONS

open access: yesUral Mathematical Journal, 2018
The paper provides a brief historical analysis of problems that use the Hausdorff distance; provides an analysis of the existing Hausdorff distance optimization elements for convex polygons; and demonstrates an optimization approach.
Dmitry I. Danilov, Alexey S. Lakhtin
doaj   +1 more source

Hausdorff Distance evaluation of orthodontic accessories' streaking artifacts in 3D model superimposition

open access: yesBrazilian Oral Research, 2012
The aim of this study was to determine whether image artifacts caused by orthodontic metal accessories interfere with the accuracy of 3D CBCT model superimposition.
José Rino Neto   +4 more
doaj   +1 more source

One‐Class Autoencoders for Porcelain Art Attribution: The Case of William Billingsley

open access: yesArchaeometry, EarlyView.
ABSTRACT This comprehensive study explores the application of advanced machine learning techniques, specifically one‐class autoencoders, for the authentication and attribution of English porcelain artworks. Focusing primarily on the works of William Billingsley (1758–1828), one of England's most celebrated porcelain decorators, we demonstrate how ...
Hassan Ugail   +3 more
wiley   +1 more source

Isodiametric inequality in Carnot groups

open access: yes, 2010
The classical isodiametric inequality in the Euclidean space says that balls maximize the volume among all sets with a given diameter. We consider in this paper the case of Carnot groups.
Rigot, Severine
core   +4 more sources

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

open access: yesComputer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier   +5 more
wiley   +1 more source

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