Results 101 to 110 of about 5,189 (241)

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

open access: yesAdvanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser   +6 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Color‐Pure Organic Luminophores: Characteristics, Definitions, Physical Basis and Fundamental Design Principles

open access: yesAngewandte Chemie, EarlyView.
Color‐pure all‐organic emitters, i.e., with narrow spectral characteristics, are intensively studied for high‐definition organic LEDs and multi‐color bioimaging. In order to guide targeted materials design, this educative review discusses spectral characteristics, proper definitions and units, and the physical basis of spectral broadening, to distill ...
Johannes Gierschner   +6 more
wiley   +2 more sources

Harnessing Machine Learning to Understand and Design Disordered Solids

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Statistical Topology and its Application to Deriving New Geometric Invariants

open access: yes
Statistical Topology and its Application to Deriving New Geometric Invariants. This project will offer a great opportunity for talented students to engage in internationally competitive research.

core  

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia   +2 more
wiley   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

open access: yesAdvanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang   +9 more
wiley   +1 more source

On area comparison and rigidity involving the scalar curvature [PDF]

open access: yes
In this thesis we study the effects of lower bounds for the curvature of a Riemannian manifold M on the geometry and topology of closed, minimal hypersurfaces.
Moraru, Vlad
core  

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

open access: yesAdvanced Intelligent Systems, EarlyView.
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
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

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