Results 181 to 190 of about 10,090 (236)

Machine-Learning-Guided Design of Incommensurate Antiferroelectrics via Field-Driven Phase Engineering. [PDF]

open access: yesAdv Sci (Weinh)
Xu K   +9 more
europepmc   +1 more source

In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs

open access: yesAdvanced Intelligent Discovery, EarlyView.
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley   +1 more source

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

open access: yesAdvanced Intelligent Systems, EarlyView.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti   +4 more
wiley   +1 more source

Predicting Crystal Structures and Ionic Conductivities in Li3YCl6−xBrx Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential

open access: yesAdvanced Intelligent Systems, EarlyView.
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley   +1 more source

Digital Twin Applications in Diabetes Management: Scoping Review. [PDF]

open access: yesJMIR Diabetes
Sarani Rad F   +4 more
europepmc   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison   +4 more
wiley   +1 more source

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