Image processing of multiphase images obtained via X‐ray microtomography: A review

S Schlüter, A Sheppard, K Brown… - Water Resources …, 2014 - Wiley Online Library
Easier access to X‐ray microtomography (μCT) facilities has provided much new insight
from high‐resolution imaging for various problems in porous media research. Pore space …

Multiscale X-ray tomography of cementitious materials: A review

S Brisard, M Serdar, PJM Monteiro - Cement and Concrete Research, 2020 - Elsevier
X-ray computed tomography (CT) is a non-destructive technique that offers a 3D insight into
the microstructure of thick (opaque) samples with virtually no preliminary sample …

Privacy and security issues in deep learning: A survey

X Liu, L Xie, Y Wang, J Zou, J Xiong, Z Ying… - IEEE …, 2020 - ieeexplore.ieee.org
Deep Learning (DL) algorithms based on artificial neural networks have achieved
remarkable success and are being extensively applied in a variety of application domains …

Masked face recognition with convolutional neural networks and local binary patterns

HN Vu, MH Nguyen, C Pham - Applied Intelligence, 2022 - Springer
Face recognition is one of the most common biometric authentication methods as its
feasibility while convenient use. Recently, the COVID-19 pandemic is dramatically …

[HTML][HTML] Evaluation of compressive properties of SLM-fabricated multi-layer lattice structures by experimental test and μ-CT-based finite element analysis

H Lei, C Li, J Meng, H Zhou, Y Liu, X Zhang, P Wang… - Materials & Design, 2019 - Elsevier
The influence of inherent imperfections should be systematically investigated to ensure the
safety and utilization of additive manufacturing-fabricated multi-scale parts and structures …

Specifics of the data processing of precession electron diffraction tomography data and their implementation in the program PETS2. 0

L Palatinus, P Brázda, M Jelínek, J Hrdá… - … Section B: Structural …, 2019 - journals.iucr.org
Electron diffraction tomography (EDT) data are in many ways similar to X-ray diffraction data.
However, they also present certain specifics. One of the most noteworthy is the specific …

Hyperspectral image classification with Markov random fields and a convolutional neural network

X Cao, F Zhou, L Xu, D Meng, Z Xu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper presents a new supervised classification algorithm for remotely sensed
hyperspectral image (HSI) which integrates spectral and spatial information in a unified …

A reproducible evaluation of ANTs similarity metric performance in brain image registration

BB Avants, NJ Tustison, G Song, PA Cook, A Klein… - Neuroimage, 2011 - Elsevier
The United States National Institutes of Health (NIH) commit significant support to open-
source data and software resources in order to foment reproducibility in the biomedical …

Regularization by denoising: Clarifications and new interpretations

ET Reehorst, P Schniter - IEEE transactions on computational …, 2018 - ieeexplore.ieee.org
Regularization by denoising (RED), as recently proposed by Romano, Elad, and Milanfar, is
powerful image-recovery framework that aims to minimize an explicit regularization objective …

Bilateral filtering for gray and color images

C Tomasi, R Manduchi - … on computer vision (IEEE Cat. No …, 1998 - ieeexplore.ieee.org
Bilateral filtering smooths images while preserving edges, by means of a nonlinear
combination of nearby image values. The method is noniterative, local, and simple. It …