BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Europe/Warsaw
BEGIN:DAYLIGHT
DTSTART:20170326T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20171029T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20180208T220217Z
UID:F402D0A5-E5B6-11E7-833E-0050568D7F66
DTSTART;TZID=Europe/Warsaw:20170922T090000
DTEND;TZID=Europe/Warsaw:20170922T094500
DESCRIPTION:Classical methods for processing and analysis of multidimension
 al signals – such as color videos and hyperspectral images – do not ex
 ploit full information contained in inner their factors. On the other hand
 \, recently developed tensor based methods allow for data representation a
 nd analysis which directly account for data multidimensionality. Examples 
 can be found in many applications such as face recognition\, image synthes
 is\, video analysis\, surveillance systems\, sensor networks\, data stream
  analysis\, marketing and medical data analysis\, to name a few.\nThis tal
 k will be focused on presentation of the basic ideas\, as well as recent a
 chievements\, in the domain of tensor based signal processing. A systemati
 c overview of tensor data representation\, tensor decompositions\, as well
  as pattern recognition with tensors will be presented. Practical aspects 
 and tensor implementation issues will be also discussed.\n\nSpeaker(s): Bo
 guslaw Cyganek\, \n\nPoznan\, Wielkopolskie\, Poland
LOCATION:Poznan\, Wielkopolskie\, Poland
ORGANIZER:tomasz.marciniak@put.poznan.pl
SEQUENCE:1
SUMMARY:[Legacy Report] Image and Video Processing with Tensor Methods
URL;VALUE=URI:https://events.vtools.ieee.org/m/152552
X-ALT-DESC:Description: <br /><p>Classical methods for processing and analy
 sis of multidimensional signals &ndash\; such as color videos and hyperspe
 ctral images &ndash\; do not exploit full information contained in inner t
 heir factors. On the other hand\, recently developed tensor based methods 
 allow for data representation and analysis which directly account for data
  multidimensionality. Examples can be found in many applications such as f
 ace recognition\, image synthesis\, video analysis\, surveillance systems\
 , sensor networks\, data stream analysis\, marketing and medical data anal
 ysis\, to name a few.<br />This talk will be focused on presentation of th
 e basic ideas\, as well as recent achievements\, in the domain of tensor b
 ased signal processing. A systematic overview of tensor data representatio
 n\, tensor decompositions\, as well as pattern recognition with tensors wi
 ll be presented. Practical aspects and tensor implementation issues will b
 e also discussed.</p>
END:VEVENT
END:VCALENDAR