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SUMMARY:Daniel Pelt\, CWI Amsterdam
DTSTART;VALUE=DATE-TIME:20190404T113000Z
DTEND;VALUE=DATE-TIME:20190404T120500Z
DTSTAMP;VALUE=DATE-TIME:20260525T050359Z
UID:indico-contribution-713@lindico453.srv.lu.se
DESCRIPTION:Improving Tomographic Reconstruction and Analysis Using Mixed-
 Scale Dense Convolutional Neural Networks\n\nIn tomography\, acquired proj
 ection data are often limited in one or more ways due to unavoidable exper
 imental constraints\, leading to inaccurate images. Using machine learning
  to improve image quality in tomography is a recently proposed solution\, 
 for which promising results have been shown. In this talk\, I will present
  the use of Mixed-Scale Dense convolutional neural networks to improve tom
 ographic reconstruction from (severely) limited data\, and present a new s
 oftware package for training and applying such networks in practice.\n\nht
 tps://lindico453.srv.lu.se/event/120/contributions/713/
LOCATION:LINXS Workshop room\, 5th floor
URL:https://lindico453.srv.lu.se/event/120/contributions/713/
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