BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Doga Gursoy
DTSTART;VALUE=DATE-TIME:20190404T124000Z
DTEND;VALUE=DATE-TIME:20190404T131500Z
DTSTAMP;VALUE=DATE-TIME:20260524T194303Z
UID:indico-contribution-122-716@lindico453.srv.lu.se
DESCRIPTION:TomoPy and related tools\n\nhttps://lindico453.srv.lu.se/event
 /120/contributions/716/
LOCATION:LINXS Workshop room\, 5th floor
URL:https://lindico453.srv.lu.se/event/120/contributions/716/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Daniel Pelt\, CWI Amsterdam
DTSTART;VALUE=DATE-TIME:20190404T113000Z
DTEND;VALUE=DATE-TIME:20190404T120500Z
DTSTAMP;VALUE=DATE-TIME:20260524T194303Z
UID:indico-contribution-122-713@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/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jonas Adler\, KTH Stockholm
DTSTART;VALUE=DATE-TIME:20190404T120500Z
DTEND;VALUE=DATE-TIME:20190404T124000Z
DTSTAMP;VALUE=DATE-TIME:20260524T194303Z
UID:indico-contribution-122-714@lindico453.srv.lu.se
DESCRIPTION:ODL for Machine learning based tomographic image reconstructio
 n\n\nODL is a python library for inverse problems developed jointly by sev
 eral research groups and companies. We introduce ODL and how it can be use
 d for variational reconstruction in inverse problems and further demonstra
 te how ODL can be used as a building block in learned iterative reconstruc
 tion methods and for learned optimization.\n\nhttps://lindico453.srv.lu.se
 /event/120/contributions/714/
LOCATION:LINXS Workshop room\, 5th floor
URL:https://lindico453.srv.lu.se/event/120/contributions/714/
END:VEVENT
END:VCALENDAR