Results 61 to 70 of about 324 (121)

Diagnostic Accuracy of Entropy Based Image Analysis of Cervical Precancerous Cells

Journal of Biophotonics, Volume 19, Issue 6, June 2026.
This work studies the correlation between the Bragg‐Williams order parameter (S2), as measured from a digital slide image, and the cytopathologic diagnoses of squamous cervical cytology and demonstrates the diagnostic accuracy of the S2 classification model. This image is an example of this approach for a “carcinoma in situ” cell image and demonstrates
Jennifer Makin, Esther Elishaev, Steven M. Durbin, Robert A. Makin   +3 more
wiley   +1 more source

Neural network with signal parameters featuring for near‐surface velocity model building

Near Surface Geophysics, Volume 24, Issue 3, Page 289-299, June 2026.
Abstract This study presents a method that integrates spectral recomposition (SR) with a neural network to improve near‐surface seismic analysis. The approach incorporates SR‐derived wavelet‐timing attributes into a fully convolutional network (FCN) to enhance the characterization of shallow subsurface structures. Field evaluation was conducted using S‐
Nelson Ricardo Coelho Flores Zuniga
wiley   +1 more source

Drone‐Based Inspection of Wind Turbine Blades: A Comparative Study of Deep Learning Models

Wind Energy, Volume 29, Issue 6, June 2026.
ABSTRACT Maintaining wind turbine blades is a challenging task, often marked by high costs, safety risks, time inefficiency, and the possibility of incorrect diagnosis. A promising approach to support preventive maintenance involves the use of drones and deep learning for inspection and early fault detection.
Lakhdar Laib, Thameur Obaidi, Mohamed Elbar, Toufik Tayeb Naas, Ahmed Bensaci, Leliso Hobicho Dabelo   +5 more
wiley   +1 more source

Inferring Internal Structures of Porous Media From Orthogonal External Surfaces: A Novel 2D‐to‐3D Reconstruction Method Based on a Deep Conditional Diffusion Model

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.
Abstract Diffusion models, a class of generative models renowned for producing realistic images, hold significant promise for reconstructing complex three‐dimensional (3D) porous media. Nevertheless, existing approaches predominantly generate stochastic microstructures visually resembling the training data but often struggle to accurately recover ...
Yinquan Meng, Jianguo Jiang, Benzhong Zhao, Shujun Ye, Dong Wang, Jichun Wu   +5 more
wiley   +1 more source

EEG complexity analysis using enhanced entropy features for depression detection and severity classification. [PDF]

J Neuroeng Rehabil
Shirazi DM, Mohebbi M, Abolfathi Y, Rostami R.   +3 more
europepmc   +1 more source

Fault diagnosis of aero-engines using transfer dispersion entropy and dispersion patterns. [PDF]

PLoS One
Zhang H, Zhang Y, Liu J, Dong K.
europepmc   +1 more source

Forecasting of interval carbon price in China based on decomposition-reconstruction-ensemble framework. [PDF]

Carbon Balance Manag
Hu B, Cheng Y.
europepmc   +1 more source

Research on Three-Phase Asynchronous Motor Fault Diagnosis Based on Multiscale Weibull Dispersion Entropy. [PDF]

Entropy (Basel), 2023
Xie F, Sun E, Zhou S, Shang J, Wang Y, Fan Q.   +5 more
europepmc   +1 more source

Stock Forecasting Based on Informational Complexity Representation: A Framework of Wavelet Entropy, Multiscale Entropy, and Dual-Branch Network. [PDF]

Entropy (Basel)
Tian G, Xu C, Yang Y.
europepmc   +1 more source

Advancing entropy analysis for heart rate variability: clinical insights for aging and diabetes. [PDF]

Front Physiol
Yang S, Wu H, Liao X, Lin Y, Liou JJ.
europepmc   +1 more source