Results 31 to 40 of about 338 (182)

Synchrotron‐Based Deep Learning Network of the Inner Ear: Development and Expert Validation

The Laryngoscope, EarlyView.
A deep learning network to automatically segment the inner ear from preoperative clinical scans was developed using synchrotron‐radiation phase contrast imaging (SR‐PCI). On an unseen test set, the network significantly outperformed seven expert otologists/radiologists, the mean expert segmentation, and a simultaneous truth and performance level ...
Ashley Micuda, Kyle Rioux, Luke Helpard, Munir Demir Bajin, Zahra Kassam, Sachin Pandey, Jaehyun Hwang, Griselda T. Romero‐Sanchez, Manas Sharma, Lorne S. Parnes, Hanif M. Ladak, Sumit K. Agrawal   +11 more
wiley   +1 more source

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

Laser &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

A Note on Sobolev‐Lorentz Capacity and Hausdorff Measure

Mathematische Nachrichten, EarlyView.
ABSTRACT In this paper, we give an elementary proof that sets of zero p,1$p,1$‐Sobolev‐Lorentz capacity are Hn−p$\mathcal {H}^{n-p}$‐null sets, independently of nonlinear potential theory. We further show that there exists a set of Sobolev‐Lorentz‐(p,1)$(p,1)$ capacity equal to zero with Hausdorff dimension equal n−p$n-p$.
Daniel Campbell
wiley   +1 more source

Relationship Between Limiting K‐Spaces and J‐Spaces in the Real Interpolation

Mathematische Nachrichten, EarlyView.
ABSTRACT In the paper, “Description of the K$K$‐Spaces by Means of J$J$‐Spaces and the Reverse Problem,” Mathematische Nachrichten 296, no. 9 (2023), 4002–4031, we have established conditions under which the limiting K$K$‐space (X0,X1)0,q,b;K$(X_0,X_1)_{0,q,b;K}$, involving a slowly varying function b$b$, can be described by means of the J$J$‐space (X0,
Bohumír Opic, Manvi Grover
wiley   +1 more source

Fractional Moment Theory for Anomalous Transport: A Unified Framework for Lévy Flights, Fractals, and Complex Dynamical Systems

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT We develop a unified mathematical framework extending classical moment theory from discrete integer orders to a continuous spectrum of real orders f>0$$ f>0 $$, providing a systematic statistical characterization of complex systems exhibiting power‐law behavior.
Farrukh A. Chishtie
wiley   +1 more source

Square packings and rectifiable doubling measures

Discrete Analysis
Square packings and rectifiable doubling measures, Discrete Analysis 2025:3, 40 pp. A measure $\mu$ on a metric space is $m$-rectifiable if it assigns full measure to a countable collection of Lipschitz images of bounded subsets of $\mathbb{R}^m ...
Matthew Badger, Raanan Schul
doaj   +1 more source

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

Otolaryngology–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, Flora Su, Norbert Banyi, Philip Edgcumbe, Andrew Thamboo, Ameen Amanian   +5 more
wiley   +1 more source

Hausdorff, Packing and Capacity Dimensions [PDF]

, 1989
In this thesis, Hausdorff, packing and capacity dimensions are studied by evaluating sets in the Euclidean space R^. Also the lower entropy dimension is calculated for some Cantor sets. By incorporating technics of Munroe and of Saint Raymond and Tricot,
Spear, Donald W.
core  

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

Archaeometry, 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, Morgan Denyer, Rachel Denyer, Howell Edwards   +3 more
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

Computer 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, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source