scholarly journals Multispectral Photoacoustic Imaging Artifact Removal and Denoising Using Time Series Model-Based Spectral Noise Estimation

2016 ◽  
Vol 35 (9) ◽  
pp. 2151-2163 ◽  
Author(s):  
Agne Kazakeviciute ◽  
Chris Jun Hui Ho ◽  
Malini Olivo
Keyword(s):  
Time Series ◽  
Photoacoustic Imaging ◽  
Time Series Model ◽  
Noise Estimation ◽  
Artifact Removal ◽  
Model Based ◽  
Imaging Artifact

Unet-based for Photoacoustic Imaging Artifact Removal

2020 ◽  
Author(s):  
Jianguang Deng ◽  
Jinchao Feng ◽  
Zhe Li ◽  
Zhonghua Sun ◽  
Kebin Jia
Keyword(s):  
Photoacoustic Imaging ◽  
Artifact Removal ◽  
Imaging Artifact

Time Series Model Based Earning Forecasting

2013 ◽  
Vol 791-793 ◽  
pp. 2147-2150
Author(s):  
Xiang Rong Jiang ◽  
Ying Ying Cui
Keyword(s):  
Time Series ◽  
Empirical Study ◽  
Relative Stability ◽  
Listed Companies ◽  
Time Series Model ◽  
New Method ◽  
Time Series Models ◽  
Seasonal Patterns ◽  
Model Based ◽  
Over Time

We propose a procedure to forecast earning of listed companies. It is a modification of method developed for forecasting series with stable seasonal patterns. The new method is motivated by the observations that seasonal patterns, which may be evolving over time and remain relative stability, arise in finance market. The method can be applied to forecast individual observations as well as the end-of-season totals. Empirical study will be conducted with data from finance market to evaluate the performance of the proposed method. The new method is proved more effective than traditional time series models.

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