Results 161 to 170 of about 561,233 (305)
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
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu +2 more
wiley +1 more source
Experimental Evidence for Edge-Mediated Microclimatic Refuge in a Southern Range Margin Population of <i>Silene regia</i>. [PDF]
Brooks MN +4 more
europepmc +1 more source
A multimodal laser‐induced graphene (LIG)‐based flexible sensor is developed to detect proximity and contact signals. Integrated into a soft robotic hand, it enables vision‐free object searching and grasping. Combined with a convolutional neural network, the system achieves accurate material and texture recognition, enhancing the capability of ...
Youning Duo +9 more
wiley +1 more source
Tree Height Prediction Using a Double Hidden-Layer Neural Network and a Mixed-Effects Model. [PDF]
Shen J, Lei X, Li Y, Pan Y, Wang G.
europepmc +1 more source
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov +8 more
wiley +1 more source
Optimizing Forest Aboveground Biomass Models with Multi-Parameter Integration. [PDF]
Liu X, Zhao Y.
europepmc +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source
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
Target-less registration of UAV-LiDAR point clouds based on graph matching of tree locations in forest environments. [PDF]
Fekry R +4 more
europepmc +1 more source

