Results 151 to 160 of about 20,368 (248)

Space Correlation Constrained Physics Informed Neural Network for Seismic Tomography

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Physics‐informed neural networks (PINNs) integrate physical constraints with neural architectures and leverage their nonlinear fitting capabilities to solve complex inverse problems. Tomography serves as a classic example, aiming to reconstruct subsurface velocity models to improve seismic exploration.
Yonghao Wang, Zhuo Jia, Bowu Jiang, Wenkai Lu   +3 more
wiley   +1 more source

MicroDeblurNet: high-fidelity restoration of spatially variant defocus in microscopic images for cucumber downy mildew. [PDF]

Plant Methods
Zhang Y, Wang B, Song Y, Han Z, Zhang X, Zhang L.   +5 more
europepmc   +1 more source

CNXT‐Ti‐LT–Based Multi‐Scale Feature–Aware Susceptibility Mapping of Rainfall‐Induced Clustered Landslides in Southeast China

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract This study focuses on the clustered landslide event triggered by intense rainfall on 16 June 2024 in the Fujian–Guangdong–Jiangxi border region, aiming to develop an efficient deep learning model for high‐accuracy landslide susceptibility mapping. Based on the mapped landslide distribution and insights from field investigations, we constructed
Senlin Luo, Wuwei Mao, Zhiqiang Yang, Guoming Zheng, Zhonghui He, Jiahuang Wang, Yu Huang   +6 more
wiley   +1 more source

A Fast Nonlinear Sparse Model for Blind Image Deblurring. [PDF]

J Imaging
Zhang Z, Guo Z, Xu Z, Chen H, Wang C, Song Y, Lai J, Ji Y, Li Z.   +8 more
europepmc   +1 more source

Global Sensitivity Analysis for Robust XAI: Quantifying Clinical Risk and Prediction Instability in Dermoscopic Image Classification

Risk Analysis, Volume 46, Issue 4, April 2026.
ABSTRACT The high nominal accuracy achieved by deep learning models in predicting malignant skin lesions is frequently undermined by their susceptibility to operational uncertainty. Image acquisition conditions, such as lighting, device settings, and skin characteristics, introduce variations in optical parameters that compromise the model's ...
Giulia Vannucci, Renato Patrik Williame Coppolecchia, Roberta Siciliano   +2 more
wiley   +1 more source

Enhanced real-time 6d pose estimation for automatic recovery of in-flight UAVs using distance-aware keypoint heatmaps. [PDF]

Sci Rep
Jeong M, Choi AJ.
europepmc   +1 more source

Shadows in the Spotlight: Casting Deep Learning Models to Unveil the Geometry of Printed Structures

Solar RRL, Volume 10, Issue 6, 29 March 2026.
A modular deep learning (DL) pipeline predicts high‐resolution geometrical finger profiles from full surface optical and laser shadow images of solar cells. All DL models combined predict finger width, height, and cross‐sectional area, validated by microscopic measurements. Resulting quality maps visualize printing errors across solar cells, enabling a
Leslie Kurumundayil, Doga Can Öner, Theresa Trötschler, Jonas Schönauer, Stefan J. Rupitsch, Ralf Preu, Stefan Rein, Matthias Demant   +7 more
wiley   +1 more source

Real-Time Endoscopic Video Enhancement via Degradation Representation Estimation and Propagation. [PDF]

J Imaging
Xu H, Nie Z, Peng T, Liu XJ.
europepmc   +1 more source

Enabling High‐Fidelity Wave‐Particle Interaction Studies: A Novel Filtering for Isolating Whistlers From Spacecraft Noise

Geophysical Research Letters, Volume 53, Issue 5, 16 March 2026.
Abstract Resolving the mixture of natural plasma waves and persistent spacecraft interference is a fundamental challenge in space physics, as it obstructs the analysis of wave‐particle interactions and energy transport processes. Traditional signal decomposition methods often fail to adequately separate these components due to their time‐varying ...
Fulin Shi, Li Zeng, Yuhui Fu, Jinbin Cao, Zhima Zeren, Dapeng Liu, Dehe Yang   +6 more
wiley   +1 more source

OpenEar: an ultra-affordable, high-throughput, and accurate maize ear phenotyping system. [PDF]

Plant Methods
Fan S, Li G, Bahitwa R, Jia Z, Zhang H, Shao J, Yu Q, Chen X, Qian Y, Xu M, Zhu L, Wang H.   +11 more
europepmc   +1 more source