[Cyverse.Nappn] [webinar] Charilaos Kanatsoulis, Friday, July 24, 10:00 am EDT (UTC -4:00)

[Tabb, Amy]

Hello NAPPN'ers,



Please see this webinar announcement for this Friday, July 24, 2020, from the technical committee on Agricultural Robotics and Automation (AgRA).  These webinars are free and open to the public; feel free to forward to interested colleagues.  Best A





Charilaos Kanatsoulis, from the University of Minnesota, USA, will present, "Hyperspectral Super-resolution: A Tensor Factorization Approach," on Friday, July 24 at 10:00 am EDT (UTC -4:00).



For easy conversions to your time zone, see this converter

fromtimeanddate.com: https://www.timeanddate.com/worldclock/fixedtime.html?msg=AgRA+Webinar+%2356%3A+Charilaos+Kanatsoulis&iso=20200724T10&p1=263&ah=1



The webinar will be provided through Zoom.  Please register:

https://us02web.zoom.us/webinar/register/1315940611334/WN_lo3w0mRCSU2-YzztfU7-Gw



Alternatively, you may view through YouTube live, which has a lower

bandwidth requirement than Zoom.  To get the link, check the technical

committee's Twitter account up to 15 minutes prior to the start of the

webinar: https://twitter.com/AgRoboticsTC



Abstract:



Hyperspectral super-resolution refers (HSR) to the problem of producing

a super-resolution image (SRI) of high spatial and spectral resolution.

The task is very well-motivated, since super-resolution images are of

great interest to multiple applications in agricultural analytics and

remote sensing. However, hardware limitations of multiband sensors

render the problem significantly costly and challenging. A natural way

to overcome this issue is by fusing a hyperspectral image (HSI) and a

multispectral image (MSI) to produce an SRI that admits fine spatial and

spectral resolutions. This inverse problem remains ill-posed, since the

number of pixels in hyperspectral and multispectral images combined, are

fewer that those required for super-resolution. In this talk, the

super-resolution problem is tackled from a tensor perspective. The

multidimensional structure of the HSI and MSI is utilized to propose a

coupled tensor factorization framework that is guaranteed to recover the

SRI. Furthermore, this tensor approach operates with relaxed modelling

assumptions compared to what was previously considered state-of-the-art.

The proposed tensor framework works remarkably well under various and

challenging scenarios and provides a new tool in the powerful multi-band

imaging toolbox.



All details, including the time zone converter, technical details, and

presenter biography available at the AgRA TC webpage:



http://ieeeagra.com/events/webinar-july-24-2020/




Amy Tabb Ph.D.
Research Engineer

United States Department of Agriculture,
Agricultural Research Service,
Appalachian Fruit Research Station

she/her
preferred address: Amy
if you really want to use a title and family name: Dr. Tabb

Mailing:
USDA-ARS-AFRS
2217 Wiltshire Rd
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304-620-5645 cell
amy.tabb at usda.gov<mailto:amy.tabb at usda.gov>
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