Results 161 to 170 of about 4,047,749 (292)
From Artificial to Embodied and Physical Intelligence in Smart Manufacturing
Smart manufacturing is reframed through complementary artificial, embodied, and physical intelligence, spanning computational reasoning, perception‐action coupling, and material‐level adaptation. Their integration across design, fabrication, operation, and maintenance reveals how intelligence can be co‐designed across algorithms, embodied agents, and ...
Kang Wang +9 more
wiley +1 more source
Harnessing Real-Time UV Imaging and Convolutional Neural Networks (CNNs): Unlocking New Opportunities for Empirical In Vitro-In Vivo Relationship Modelling. [PDF]
Stróżyk M, Pacławski A, Mendyk A.
europepmc +1 more source
An AI‐Driven Framework for Directed Self‐Assembly Toward Design‐Technology Co‐Optimization
An artificial intelligence (AI)‐driven closed‐loop framework integrates experiment, three‐dimensional physics‐based simulation, and template design for directed self‐assembly (DSA). Guided by experimental data, AI‐assisted calibration accelerates model optimization, supports morphology prediction, and identifies template windows.
Caiwei Shang +9 more
wiley +1 more source
Evaluation of Convolutional Neural Networks (CNNs) in Identifying Retinal Conditions Through Classification of Optical Coherence Tomography (OCT) Images. [PDF]
Teegavarapu RR +5 more
europepmc +1 more source
A multifunctional vertical bulk‐heterojunction transistor (MVBT) with amorphous GaOx integrates four functionalities within a single neuromorphic device. Gate‐source operation enables 254 nm deep‐ultraviolet sensing and threshold neuronal firing, whereas three‐terminal operation supports broadband UV–vis‐NIR synaptic functions and bias‐controlled ...
Jinkui Si +12 more
wiley +1 more source
Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (<i>Pennisetum glaucum</i>). [PDF]
Dhawi F +4 more
europepmc +1 more source
XChrom is a deep learning framework that integrates genomic sequence and single‐cell context to predict chromatin accessibility. It generalizes to unseen cells and genomic regions, enabling cross‐sample and cross‐species analysis. Applied to COVID‐19 patient data, XChrom reveals key transcriptional regulatory mechanisms and disease‐associated ...
Yuanyuan Miao +5 more
wiley +1 more source
This study establishes perineural invasion density (PNID) as a superior prognostic marker in prostate cancer, outperforming conventional perineural invasion in predicting biochemical recurrence and radiographic progression. Concurrent β–blocker use is associated with favorable outcomes exclusively in High–PNID patients. An MRI–based deep learning model
Bohao Liu +20 more
wiley +1 more source
Convolutional neural network(CNN)モデル
OHNO, Ken, MATSUMOTO, Kentaro
openaire +1 more source
Subclinical matrix disruption precedes degenerative meniscal tears across the knee joint. A spatial compartmental radiomics model utilizing 3D‐DESS MRI captures early osteochondral destabilization, accurately predicting incident tears up to four years pre‐collapse. Feature attributions uncover coordinated chondral and osseous alterations, advancing non‐
Shengfa Li +13 more
wiley +1 more source

