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DTSTAMP:20200911T173726Z
UID:314411F0-D4A4-4239-B4D1-8274201E1012
DTSTART;TZID=US/Eastern:20200910T163000
DTEND;TZID=US/Eastern:20200910T173000
DESCRIPTION:Current trends in artificial intelligence/machine learning (AI/
 ML) have increased the interest in multi-source techniques\, especially th
 ose of multispectral image fusion. The presentation will highlight develop
 ments in image fusion applications\, methods\, and evaluation.\n\nImage fu
 sion applications include: surveillance\, medical\, and inspection utilizi
 ng multi-focus\, multi-resolution\, multi-view\, multi-exposure\, multi-sp
 ectrum\, and multi-modal data. Image fusion methods include statistical pr
 ocessing\, wavelet transforms as well as recent methods with generative ad
 versarial networks (GANs). Evaluation includes data sets and collection\, 
 performance metrics\, and quantitative and qualitative performance.\n\nThe
  talk will focus on basic methods and approaches\, provide examples\, and 
 discuss guidelines as well as recent trends in image fusion. Examples and 
 references will be provided so as to point the audience to more details on
  fundamental constructs towards their areas of interest.\n\nCo-sponsored b
 y: CH02182 - Washington/Baltimore/No VA Jt Sections Chap\,CAS04\n\nSpeaker
 (s): Erik Blasch\, PhD\, MBA\, \n\nVirtual: https://events.vtools.ieee.org
 /m/238351
LOCATION:Virtual: https://events.vtools.ieee.org/m/238351
ORGANIZER:tomburkeii@gmail.com
SEQUENCE:1
SUMMARY:Multispectral Image Fusion
URL;VALUE=URI:https://events.vtools.ieee.org/m/238351
X-ALT-DESC:Description: <br /><p>Current trends in artificial intelligence/
 machine learning (AI/ML) have increased the interest in multi-source techn
 iques\, especially those of multispectral image fusion. The presentation w
 ill highlight developments in image fusion applications\, methods\, and ev
 aluation.</p>\n<p>Image fusion applications include: surveillance\, medica
 l\, and inspection utilizing multi-focus\, multi-resolution\, multi-view\,
  multi-exposure\, multi-spectrum\, and multi-modal data.&nbsp\; Image fusi
 on methods include statistical processing\, wavelet transforms as well as 
 recent methods with generative adversarial networks (GANs). Evaluation inc
 ludes data sets and collection\, performance metrics\, and quantitative an
 d qualitative performance.&nbsp\;</p>\n<p>The talk will focus on basic met
 hods and approaches\, provide examples\, and discuss guidelines as well as
  recent trends in image fusion. Examples and references will be provided s
 o as to point the audience to more details on fundamental constructs towar
 ds their areas of interest.&nbsp\;</p>
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