BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.19//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20180311T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20181104T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20191002T140000
DTEND;TZID=America/New_York:20191002T150000
DTSTAMP:20260408T112249
CREATED:20190924T202721Z
LAST-MODIFIED:20190924T202721Z
UID:2048-1570024800-1570028400@seasevents.nmsdev7.com
SUMMARY:ESE Faculty Hosted Talk: "Deep Learned Optical Multiplexing for Microscopy"
DESCRIPTION:Abstract: Fourier ptychographic microscopy is a technique that achieves a high space-bandwidth product\, i.e. high resolution and high field-of-view. In Fourier ptychographic microscopy\, variable illumination patterns are used to collect multiple low-resolution images. These low-resolution images are then computationally combined to create an image with resolution exceeding that of any single image from the microscope. Due to the necessity of acquiring multiple low-resolution images\, Fourier ptychographic microscopy has poor temporal resolution. Our aim is to improve temporal resolution in Fourier ptychographic microscopy\, achieving single-shot imaging without sacrificing space-bandwidth product. We use physical preprocessing and example-based super-resolution to achieve this goal by trading off generality of the imaging approach. \nIn example-based super-resolution\, the function relating low-resolution images to their high-resolution counterparts is learned from a given dataset. We take the additional step of optimizing the imaging hardware in order to collect more informative low-resolution images. We show that this “physical preprocessing” allows for improved image reconstruction with deep learning in Fourier ptychographic microscopy.
URL:https://seasevents.nmsdev7.com/event/ese-faculty-hosted-talk-deep-learned-optical-multiplexing-for-microscopy/
LOCATION:Room 307\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
END:VCALENDAR