Results 181 to 190 of about 90,452 (269)
A common framework for semantic memory and semantic composition. [PDF]
Law RMC, Lambon Ralph MA, Hauk O.
europepmc +1 more source
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
The Cross-Linguistic Coordination of Overt Attention and Speech Production as Evidence for a Language of Vision. [PDF]
Coco MI, Fernandes EG, Arai M, Keller F.
europepmc +1 more source
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
Syntactic processing engages the semantic control network. [PDF]
Chang Q, Jefferies E, Jackson RL.
europepmc +1 more source
In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs
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
MFDA-UNet: Medical Image Segmentation with Frequency-Decoupled Representation and Gated Cross-Scale Integration. [PDF]
Deng W, Wu C.
europepmc +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
A framework for semantics-based situational awareness during mobile robot deployments. [PDF]
Ruan T +8 more
europepmc +1 more source

