Results 221 to 230 of about 115,549 (311)
Second law analysis of Casson Darcy-Forchheimer flow in two-phase nanomaterials with solar radiation and microbial cells using Homann mixed convection modeling. [PDF]
Kashif AN, Zaheer KB, Saeed AM, Liu H.
europepmc +1 more source
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
CSFCNet: Cascaded Spatial-Frequency Convolutional Network for Hyperspectral Image Classification. [PDF]
Jiang F, Liu X, Li M, Nie T, Huang L.
europepmc +1 more source
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
Fast automated adjoints for spectral PDE solvers. [PDF]
Skene CS, Burns KJ.
europepmc +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Fresnel reflection coefficients in the Fourier domain for a planar surface in uniform motion parallel to its interface. [PDF]
Azar S, Rodríguez-Fortuño FJ, Golat S.
europepmc +1 more source
ON APPROXIMATE: SOLVING OF THE FOURIER PROBLEMS
openaire +1 more source
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Energy-dissipative adaptive-step L1 discretisation for the Caputo time-fractional incompressible magnetohydrodynamic system. [PDF]
Abidin MZ.
europepmc +1 more source

