Results 41 to 50 of about 1,786 (118)

Optimised Random Forest Classifier for Fibre Tracking With Fibre Separation in an Orientation Process

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.
ABSTRACT This work presents a fibre tracking process based on a Random Forest classifier. This process is designed to work with minimal labelled data while achieving robust performance. Unlike data‐intensive AI methods, our approach focuses on careful feature selection and iterative optimisation to improve the algorithm.
Tim Vaupel, Ann Mary Neethu, Olaf Wünsch   +2 more
wiley   +1 more source

Time course sensor‐based phenotyping can predict Ascochyta blight disease severity in Cicer species

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Ascochyta blight is a widely occurring chickpea fungal disease that can cause severe yield loss. Breeding for crop resistance benefits from high‐throughput evaluation of plant–pathogen interactions in genotypes which can serve as sources of resistance.
Florian Tanner, Judith Atieno, Sara Blake, Marzena Krysinska‐Kaczmarek, Chris Brien, Mohsen Khani, Kenneth Clarke, Darren Plett, Jennifer Davidson, Bettina Berger   +9 more
wiley   +1 more source

High‐throughput unmanned aerial vehicle phenomics and machine learning enables accurate early single‐plant biomass prediction in lettuce

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Lettuce (Lactuca sativa L.) exhibits pronounced genotype and environment‐dependent growth variation, making early, non‐destructive single‐plant biomass prediction critical for breeding. However, harvest‐based measurements fail to capture growth dynamics.
Görkem Eren Özdemir, Ahmet Rıza Ağır, Burak Aktürk, Nida Selen Baysal, Adem Dogan, Aaron J. DeSalvio, Mustafa A. Arik, Yasin Topcu, Alper Adak   +8 more
wiley   +1 more source

Advancing the Volumetric Analysis of Ultra‐Low‐Field Brain MRI Using Image‐to‐Image Translation

Magnetic Resonance in Medicine, Volume 96, Issue 5, Page 2458-2473, November 2026.
ABSTRACT Purpose Ultra‐low‐field (ULF) MRI offers a promising path to accessible neuroimaging, with potential to address global healthcare disparities and advance population‐level brain health research. However, the inherently low signal‐to‐noise ratio (SNR), reduced spatial resolution, and altered tissue contrasts relative to conventional high‐field ...
Peter Hsu, Elisa Marchetto, Patricia M. Johnson, Jelle Veraart   +3 more
wiley   +1 more source

A Hybrid Physics‐Informed Computational Framework for Adaptive Microrobotic Navigation and Causal Structure Discovery in Simulated Non‐Newtonian Environments

Applied Research, Volume 5, Issue 5, October 2026.
This study presents a hybrid AI framework that enables autonomous magnetic microrobots to navigate complex, non‐Newtonian tumor microenvironments. By integrating physics‐informed recurrent reinforcement learning with active persistent excitation, the system successfully infers hidden fluid rheology for precise targeted navigation and structural causal ...
Xinyuan Chen, Zanariah Abu Bakar, Mohd Nizam Husen   +2 more
wiley   +1 more source

Interpreting Non‐Linear Compaction Mechanics of Expansive Soils Using Reliability Calibrated Framework

Applied Research, Volume 5, Issue 5, October 2026.
This study introduces a reliability‐calibrated machine learning framework to predict the maximum dry density and optimum moisture content of heterogeneous soils. By integrating 15 algorithms with conformal prediction, the models deliver accurate compaction estimates alongside rigorous, distribution‐free 90% confidence intervals.
Farjad Aziz, Muhammad Waseem, Zeeshan Asghar, Megersa Kebede Leta   +3 more
wiley   +1 more source

Comparison of the Cox Proportional Hazards Model and Random Survival Forest Algorithm for Predicting Patient‐Specific Survival Probabilities in Clinical Trial Data

Biometrical Journal, Volume 68, Issue 5, October 2026.
ABSTRACT The Cox proportional hazards model is often used to analyze data from randomized controlled trials (RCTs) with time‐to‐event outcomes. Random survival forest (RSF) is a machine‐learning algorithm known for its high predictive performance. We conduct a comprehensive neutral comparison study to compare the performance of Cox regression and RSF ...
Ricarda Graf, Susan Todd, M. Fazil Baksh
wiley   +1 more source

Interpolation properties of generalized perfect splines and the solutions of certain extremal problems. I [PDF]

Transactions of the American Mathematical Society, 1975
openaire   +2 more sources

Handling Experimental Data in FACPACK: Noise Effects on Duality Relations and Algorithmic Parameter Selection

Journal of Chemometrics, Volume 40, Issue 10, October 2026.
ABSTRACT The area of feasible solutions (AFS) quantifies factor ambiguity in multivariate curve resolution (MCR). Although AFS computation is well‐defined for noise‐free data, experimental datasets require constraint relaxation and parameter tuning, which influence the resulting feasible bands.
Mathias Sawall, Christoph Kubis, Alejandro Olivieri, Steven J. Roeters, Klaus Neymeyr   +4 more
wiley   +1 more source

How Much Physics Should a Neural Network Know? Thermodynamics‐Informed Neural Networks for Rock Constitutive Modeling With Epistemic Uncertainty

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Machine learning offers a flexible route to constitutive modeling, with two emergent questions for geoscience applications: what level of thermodynamic constraint should be embedded in the network architecture, and how should predictive uncertainty be quantified when extrapolating from laboratory to field conditions? We address both challenges
Kangan Li, Tushar Mittal, Benjamin K. Holtzman, Seth Saltiel   +3 more
wiley   +1 more source