Artifacts removal in LBP based flame edges using binary morphology

2015 ◽  
Author(s):  
Zakir Hussain ◽  
Diwakar Agarwal
Keyword(s):  
Artifacts Removal ◽  
Binary Morphology

scholarly journals Image Denoising and Ring Artifacts Removal for Spectral CT via Deep Neural Network

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Xiaojie Lv ◽  
Xuezhi Ren ◽  
Peng He ◽  
Mi Zhou ◽  
Zourong Long ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Denoising ◽  
Deep Neural Network ◽  
Spectral Ct ◽  
Artifacts Removal

scholarly journals Deep learning denoising for EOG artifacts removal from EEG signals

2020 ◽  
Author(s):  
Najmeh Mashhadi ◽  
Abolfazl Zargari Khuzani ◽  
Morteza Heidari ◽  
Donya Khaledyan
Keyword(s):  
Deep Learning ◽  
Eeg Signals ◽  
Artifacts Removal

Automatic ocular artifacts removal in EEG using deep learning

2018 ◽  
Vol 43 ◽  
pp. 148-158 ◽  
Author(s):  
Banghua Yang ◽  
Kaiwen Duan ◽  
Chengcheng Fan ◽  
Chenxiao Hu ◽  
Jinlong Wang
Keyword(s):  
Deep Learning ◽  
Artifacts Removal ◽  
Ocular Artifacts

Artifacts removal in EEG signal using a new neural network enhanced adaptive filter

2013 ◽  
Vol 103 ◽  
pp. 222-231 ◽  
Author(s):  
Aysa Jafarifarmand ◽  
Mohammad Ali Badamchizadeh
Keyword(s):  
Neural Network ◽  
Adaptive Filter ◽  
Eeg Signal ◽  
Artifacts Removal

Study on Dynamic Mechanical Response of TC21 Alloy

2011 ◽  
Vol 88-89 ◽  
pp. 674-678
Author(s):  
Shuang Zan Zhao ◽  
Xing Wang Cheng ◽  
Fu Chi Wang
Keyword(s):  
Flow Stress ◽  
High Strain Rate ◽  
Strain Rate ◽  
Strain Hardening ◽  
High Strain ◽  
Dynamic Flow ◽  
Dynamic Mechanical ◽  
Hardening Effect ◽  
High Strain Rate Deformation ◽  
Binary Morphology

Some results of an experimental study on high strain rate deformation of TC21 alloy are discussed in this paper. Cylindrical specimens of the TC21 alloys both in binary morphology and solution and aging morphology were subjected to high strain rate deformation by direct impact using a Split Hopkinson Pressure Bar. The deformation process is dominated by both thermal softening effect and strain hardening effect under high strain rate loading. Thus the flow stress doesn’t increase with strain rate at the strain hardening stage, while the increase is obvious under qusi-static compression. Under high strain rate, the dynamic flow stress is higher than that under quasi-static and dynamic flow stress increase with the increase of the strain rate, which indicates the strain rate hardening effect is great in TC21 alloy. The microstructure affects the dynamic mechanical properties of TC21 titanium alloy obviously. Under high strain rate, the solution and aging morphology has higher dynamic flow stress while the binary morphology has better plasticity and less prone to be instability under high strain rate condition. Shear bands were found both in the solution and aging morphology and the binary morphology.

An adaptive fuzzy filter for coding artifacts removal in video and image

2007 ◽  
Vol 8 (6) ◽  
pp. 841-848 ◽  
Author(s):  
Jing Wu ◽  
Xiu-qing Ye ◽  
Wei-kang Gu
Keyword(s):  
Fuzzy Filter ◽  
Adaptive Fuzzy ◽  
Artifacts Removal
Sign in / Sign up

Export Citation Format

Share Document