Results 41 to 50 of about 11,509,765 (247)

IMAGE DE-BLURRING USING WIENER DE-CONVOLUTION AND WAVELET FOR DIFFERENT BLURRING KERNEL

open access: yes, 2016
Image de-convolution is an active research area of recovering a sharp image after blurring by a convolution. One of the problems in image de-convolution is how to preserve the texture structures while removing blur in presence of noise.
M.Tech Research Scholar Shuchi Singh*, Asst Professor Vipul Awasthi, Asst Professor NitinSahu
core   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

open access: yesAdvanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran   +6 more
wiley   +1 more source

Image SegmentationonTextureBlurring

open access: yes工程科学与技术, 2015
:Traditionalactivecontoursegmentationalgorithmexistedover-segmentationandunder-segmentationfortexture-richimages.Inordertosuppressthetextureontheinfluenceoftheimagesegmentation,thediffusemechanismofisotropicandanisotropic was
何坤, 郑秀清, 张永来
doaj  

Application research on improved CGAN in image raindrop removal

open access: yesThe Journal of Engineering, 2019
Rainy weather can greatly reduce the image quality and hinder the subsequent processing of the image. In order to achieve raindrop removal on rainy images, the single image raindrop removal method based on conditional generative adversarial networks ...
Min Zhu   +4 more
doaj   +1 more source

Source Image s and its different degrees of blurring distorted images.

open access: yes, 2014
Source Image s and its different degrees of blurring distorted images.
Chao-Feng Li (632823)   +3 more
core   +1 more source

OntOMat: Toward Ontology‐Based Product and Process Design Engineering and Optimization Solutions Fueling Circular Value Chains

open access: yesAdvanced Engineering Materials, EarlyView.
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ   +19 more
wiley   +1 more source

Impact of Atmospheric Turbulence on Data Quality During BVLOS UAV Missions in Antarctic Conditions

open access: yesDrones
This article presents an analysis of the impact of atmospheric turbulence on the quality of images obtained during photogrammetric missions in Antarctica using a fixed-wing UAV operating in BVLOS mode.
Anna Zmarz, Mirosław Rodzewicz
doaj   +1 more source

Blind Deblurring Reconstruction Technique with Applications in PET Imaging

open access: yesInternational Journal of Biomedical Imaging, 2009
We developed an empirical PET model taking into account system blurring and a blind iterative reconstruction scheme that estimates both the actual image and the point spread function of the system. Reconstruction images of high quality can be acquired by
Heng Li   +3 more
doaj   +1 more source

Improvement of the Performance of Scattering Suppression and Absorbing Structure Depth Estimation on Transillumination Image by Deep Learning

open access: yesApplied Sciences, 2023
The development of optical sensors, especially with regard to the improved resolution of cameras, has made optical techniques more applicable in medicine and live animal research. Research efforts focus on image signal acquisition, scattering de-blur for
Ngoc An Dang Nguyen   +2 more
doaj   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

open access: yesAdvanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling   +15 more
wiley   +1 more source

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