Consistent explainable image quality assessment for medical imaging. [PDF]
Ozer C +3 more
europepmc +1 more source
Artificial Neural Networks for Defining the Operational Parameters of Sand Filters for Irrigation
ABSTRACT The difficulty in defining the working configuration during the operation of sand filters arises from the complexity of the relationships among the variables in the filtration and backwashing processes. The objective was to use artificial neural networks to model the pressure loss and removal efficiency of filtration in a commercial sand ...
Mádilo Lages Vieira Passos +4 more
wiley +1 more source
Model-Driven Processing of Passive Seismic While Drilling Data Acquired Using Distributed Acoustic Sensing Without Conventional Drill-Bit Pilot Measurements. [PDF]
Al-Hemyari E, Pevzner R, Tertyshnikov K.
europepmc +1 more source
Deep Learning Integration in Optical Microscopy: Advancements and Applications
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari +5 more
wiley +1 more source
Temporal single spike coding for effective transfer learning in spiking neural networks. [PDF]
Moqadasi H, Safari S, Mateo F.
europepmc +1 more source
3D Surface Profiling via Direct End‐to‐End Regression With a Photonic Geometric Sensor
Measurements of microscale surface patterns are essential for quality control across semiconductor and biomedical industries, yet the development of miniaturized, intelligent systems remains constrained by the complexity and bulkiness of conventional benchtop metrology.
Ziyao Zhang +13 more
wiley +1 more source
GRN+: a simplified generative reinforcement network for tissue layer analysis in 3D ultrasound images for chronic low-back pain. [PDF]
Zeng Z, Zhao X, Cartier M, Meng X, Pu J.
europepmc +1 more source
Neural networks can accelerate modeling and inverse design of electromagnetic devices by several orders of magnitude, but usually require large amounts of data to train. This work demonstrates that integrating knowledge about quasinormal modes into the network architecture reduces the required amount of training data significantly, while simultaneously
Viktor A. Lilja +3 more
wiley +1 more source
Retraction notice to "Cattaneo-Christov heat flow model at mixed impulse stagnation point past a Riga plate: Levenberg-Marquardt backpropagation method" [Heliyon 9 (2023) e22765]. [PDF]
Hussain S +6 more
europepmc +1 more source
When seeking nanoparticles with elevated drug loading content, the experimental setup, including solvent selection, is crucial. Through machine learning, we pinpointed that the drug's solubility in the organic solvent is the key factor for attaining high drug loading content.
Wei Ge +4 more
wiley +1 more source

