Results 221 to 230 of about 157,053 (258)

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

Advanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova, Steffen Brinckmann, Ruth Schwaiger   +2 more
wiley   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Benchmarking Low-Light Image Enhancement and Beyond

International Journal of Computer Vision, 2021
In this paper, we present a systematic review and evaluation of existing single-image low-light enhancement algorithms. Besides the commonly used low-level vision oriented evaluations, we additionally consider measuring machine vision performance in the low-light condition via face detection task to explore the potential of joint optimization of high ...
Jiaying Liu 0001, Dejia Xu, Wenhan Yang, Minhao Fan, Haofeng Huang   +4 more
openaire   +1 more source

Polarization-Aware Low-Light Image Enhancement

Proceedings of the AAAI Conference on Artificial Intelligence, 2023
Polarization-based vision algorithms have found uses in various applications since polarization provides additional physical constraints. However, in low-light conditions, their performance would be severely degenerated since the captured polarized images could be noisy, leading to noticeable degradation in the degree of polarization (DoP) and the ...
Chu Zhou, Minggui Teng, Youwei Lyu, Si Li 0001, Chao Xu 0006, Boxin Shi   +5 more
openaire   +1 more source

Semantically-guided low-light image enhancement

Pattern Recognition Letters, 2020
Abstract Recently, extensive research efforts have been made on low-light image enhancement. Many novel models have been proposed, such as the ones based on the Retinex theory, multiple exposure fusion, and deep neural networks. However, current models do not directly consider the semantic information in the modeling process.
Junyi Xie, Hao Bian, Yuanhang Wu, Yu Zhao, Linmin Shan, Shijie Hao   +5 more
openaire   +1 more source

Image enhancement for extremely low light conditions

2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2014
In this paper, a novel methodology is proposed for contrast enhancement and noise reduction in very noisy data with low dynamic range on images captured by surveillance camera under extremely low light condition. For the initial noise reduction, a motion adaptive temporal filtering based on the Kalman filter is employed.
Dubok Park, Minjae Kim, Bonhwa Ku, Sangmin Yoon, David K. Han   +4 more
openaire   +1 more source

Lightening Network for Low-Light Image Enhancement

IEEE Transactions on Image Processing, 2020
Low-light image enhancement is a challenging task that has attracted considerable attention. Pictures taken in low-light conditions often have bad visual quality. To address the problem, we regard the low-light enhancement as a residual learning problem that is to estimate the residual between low- and normal-light images.
Li-Wen Wang, Zhi-Song Liu, Wan-Chi Siu, Daniel Pak-Kong Lun   +3 more
openaire   +2 more sources

Low-Light Stereo Image Enhancement

IEEE Transactions on Multimedia, 2023
Jie Huang 0017, Xueyang Fu, Zeyu Xiao 0002, Feng Zhao 0004, Zhiwei Xiong   +4 more
openaire   +1 more source

Semi-Supervised Learning for Low-Light Image Enhancement by Pseudo Low-Light Image

2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2023
Shuo Xie, Yingjie Ma, Wei Xu, Song Qiu, Yifei Sun   +4 more
openaire   +1 more source

Low-light image enhancement using inverted image normalized by atmospheric light

Signal Processing, 2022
Il Kyu Eom
exaly