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publications:annualreports:saig_22 [2022/02/01 21:59]
msacchi
publications:annualreports:saig_22 [2022/02/02 02:39]
msacchi
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 ====== Individual Chapters ​ ====== ====== Individual Chapters ​ ======
  
-<fc #​008000>​SAIG 22-1 (2022) Breno Bahia</​fc>​\\+<fc #​008000>​SAIG 22-1 (2021) Breno Bahia</​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_01.pdf |Neural estimation of local slopes }} <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_01.pdf |Neural estimation of local slopes }}
 </​WRAP>​ </​WRAP>​
  
  
-<fc #​008000>​SAIG 22-2 (2022) Kristian Torres </​fc>​\\+<fc #​008000>​SAIG 22-2 (2021) Kristian Torres </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_02.pdf | Least-squares reverse-time migration via deep learning- <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_02.pdf | Least-squares reverse-time migration via deep learning-
 based updating operators }} based updating operators }}
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-<fc #​008000>​SAIG 22-3 (2022) Kristian Torres </​fc>​\\+<fc #​008000>​SAIG 22-3 (2021) Kristian Torres </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_03.pdf | Deep null space regularization for seismic inverse prob- <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_03.pdf | Deep null space regularization for seismic inverse prob-
 lems}} lems}}
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-<fc #​008000>​SAIG 22-4 (2022) Hongling Chen </​fc>​\\+<fc #​008000>​SAIG 22-4 (2021) Hongling Chen </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_04.pdf | Nonstationary Seismic Reflectivity Inversion Based on Prior-engaged Mixed Dimensional Deep Learning Method }} <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_04.pdf | Nonstationary Seismic Reflectivity Inversion Based on Prior-engaged Mixed Dimensional Deep Learning Method }}
 </​WRAP>​ </​WRAP>​
  
-<fc #​008000>​SAIG 22-5 (2022) Dawei Liu</​fc>​\\+<fc #​008000>​SAIG 22-5 (2021) Dawei Liu</​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_05.pdf | Efficient seismic scattered noise  <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_05.pdf | Efficient seismic scattered noise 
 attenuation in OVT domain: application of deep learning }} attenuation in OVT domain: application of deep learning }}
 </​WRAP>​ </​WRAP>​
  
-<fc #​008000>​SAIG 22-6 (2022) Rafael Manenti </​fc>​\\+<fc #​008000>​SAIG 22-6 (2021) Rafael Manenti </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_06.pdf | Prestack data reconstruction via CUR decomposition }} <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_06.pdf | Prestack data reconstruction via CUR decomposition }}
 </​WRAP>​ </​WRAP>​
  
-<fc #​008000>​SAIG 22-7 (2022) Yi Guo </​fc>​\\+<fc #​008000>​SAIG 22-7 (2021) Yi Guo </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_07.pdf | Data-driven optimal sparse seismic acquisition design}} <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_07.pdf | Data-driven optimal sparse seismic acquisition design}}
 </​WRAP>​ </​WRAP>​
  
  
-<fc #​008000>​SAIG 22-8 (2022) Ji Li  </​fc>​\\+<fc #​008000>​SAIG 22-8 (2021) Ji Li  </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_08.pdf | Robust reconstruction via Orthogonal Matching Pursuit <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_08.pdf | Robust reconstruction via Orthogonal Matching Pursuit
 with Fourier transform }} with Fourier transform }}
 </​WRAP>​ </​WRAP>​
  
-<fc #​008000>​SAIG 22-9 (2022) Alejandro Quiaro </​fc>​\\+<fc #​008000>​SAIG 22-9 (2021) Alejandro Quiaro </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_09.pdf |SNR based automatic rank determination and its appli- <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_09.pdf |SNR based automatic rank determination and its appli-
 cation for de-noising using MSSA }} cation for de-noising using MSSA }}
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-<fc #​008000>​SAIG 22-10 (2022) Rongzhi Lin </​fc>​\\+<fc #​008000>​SAIG 22-10 (2021) Rongzhi Lin </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_10.pdf | Iterative 3D deblending and reconstruction with inter- <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_10.pdf | Iterative 3D deblending and reconstruction with inter-
 polated MSSA (I-MSSA) for arbitrary irregular com- polated MSSA (I-MSSA) for arbitrary irregular com-
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-<fc #​008000>​SAIG 22-11 (2022) Rongzhi Lin </​fc>​\\+<fc #​008000>​SAIG 22-11 (2021) Rongzhi Lin </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_11.pdf | A comparative study of seismic reconstruction for arbi- <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_11.pdf | A comparative study of seismic reconstruction for arbi-
 trary irregular-grid acquisition:​ I-FMSSA vs. EPOCS }} trary irregular-grid acquisition:​ I-FMSSA vs. EPOCS }}
 </​WRAP>​ </​WRAP>​
  
-<fc #​008000>​SAIG 22-12 (2022) Joaquin Acedo </​fc>​\\+<fc #​008000>​SAIG 22-12 (2021) Joaquin Acedo </​fc>​\\
 <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_12.pdf | Compressed Sensing and Sparsity Promoting Inversion }} <WRAP indent>​{{:​sponsorsandstudents:​saig22r:​chap_12.pdf | Compressed Sensing and Sparsity Promoting Inversion }}
 </​WRAP>​ </​WRAP>​
publications/annualreports/saig_22.txt ยท Last modified: 2022/02/02 02:39 by msacchi