Results 11 to 20 of about 177 (131)

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

The Benjamin–Ono Equation in the Zero‐Dispersion Limit for Rational Initial Data: Generation of Dispersive Shock Waves

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone, Louise Gassot, Patrick Gérard, Peter D. Miller   +3 more
wiley   +1 more source

Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance

Naval Research Logistics (NRL), EarlyView.
ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley   +1 more source

A Machine Learning Approach to Predict Functional Performance From Measurable Protein Structural Characteristics: A Screening Tool for Protein Ingredient Quality

Proteins: Structure, Function, and Bioinformatics, EarlyView.
ABSTRACT The food industry is witnessing the emergence of specialized protein‐based functional ingredients for the use as gelling, thickening, and/or emulsifying agents in various food applications. Different sources of protein including species and cultivars, as well as variable processing conditions affect the protein's structural characteristics ...
Ronit Mandal, Sara Malvar, Ranveer Chandra, Baraem P. Ismail   +3 more
wiley   +1 more source

A CNN Approach for Simultaneous Spatiotemporal Fault Interpretation

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Convolutional Neural Networks (CNNs) have emerged as one of the most effective tools for image analysis. In this study, we propose a custom‐designed CNN architecture to construct a process control scheme based on image data. The product image is partitioned into equal‐sized grids, each comprising three channels: (i) reference image, (ii ...
Hamed Sabahno
wiley   +1 more source

A Novel Approach to Energy Management in Electric Steelworks

steel research international, EarlyView.
Feed‐forward neural networks are exploited to estimate electric energy consumptions of the electric arc furnace and ladle furnace processes. The models are used to optimize production schedule so that more energy intensive grades are produced when the cost of energy is lower.
Valentina Colla, Stefano Dettori, Silvia Cateni, Marco Vannucci, Antonella Vignali, Claudio Mocci, Irene Dovichi, Davide Chionna, Lorenzo Vannini, Enrico Paluzzano, Costanzo Pietrosanti, Davide Onesti, Daniele Venier   +12 more
wiley   +1 more source

A new smooth failure criterion for concrete inspired by Lubliner's condition

Structural Concrete, EarlyView.
Abstract A new failure criterion with 10 parameters is proposed, based on Lubliner's idea of joining two Drucker–Prager cones. The novelty lies in the way of introducing deviatoric shape variation: through two Podgórski's functions. This feature allows for improving plane stress cross‐section's compatibility with experimental data.
Inez Kamińska, Aleksander Szwed
wiley   +1 more source

AT‐AER: Adversarial Training With Adaptive Example Reuse

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Adversarial training (AT) is widely regarded as a crucial defense method for deep neural networks against adversarial attacks. Most of the existing AT methods suffer from the problems of insufficient coverage of perturbation space and robust overfitting.
Meng Hu, Yanting Guo, Ran Wang, Xizhao Wang, Rihao Li, Qin Wang   +5 more
wiley   +1 more source