Results 141 to 150 of about 706 (282)

GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li   +9 more
wiley   +1 more source

Biodegradable and Bioinspired UV Light Recognition via Sustainable Synaptic Transistors for Artificial Intelligence Vision Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
We report a biodegradable electrolyte‐gated synaptic phototransistor that combines low‐power UV sensing with memory functionality, offering a sustainable platform for AI vision systems and health‐monitoring technologies. Presented here is a biodegradable, bioinspired synaptic phototransistor (SPT) based on an electrolyte‐gated field‐effect transistor ...
Theodoros Serghiou   +5 more
wiley   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

open access: yesAdvanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella   +5 more
wiley   +1 more source

Addressing the consequences of the corporatization of reproductive medicine. [PDF]

open access: yesMed Law Rev
Attinger SA   +7 more
europepmc   +1 more source

RT‐DETR‐DA for Complex Scenes: Distracted Driving Detection With Feature Interaction and Dynamic Perception

open access: yesAdvanced Intelligent Systems, EarlyView.
This work proposes RT‐DETR‐DA, an enhanced real‐time detection framework for identifying distracted driving in complex, real‐world environments. The model introduces a dynamic sparse gating multiscale attention module and an attention‐guided dual‐path fusion module to strengthen multiscale perception and cross‐layer feature interaction.
Yi Liu   +4 more
wiley   +1 more source

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