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SUMMARY:Automatically generating structured information on the as-is statu
 s of facilities from visual data
DTSTART:20190628T103000
DTEND:20190628T113000
DTSTAMP:20260408T071137Z
UID:d0a914aa28d751b77a04e4b9f48ad916156fc1dbaccfa8e66ed7d2fc
CATEGORIES:Conferences - Seminars
DESCRIPTION:Iro Armeni | Stanford University\, USA\nDespite the large pro
 duction and collection of digital data\, the AEC/FM industry lacks accurat
 e\, detailed\, consistent and up-to-date knowledge of facilities. Advances
  in sensing technology allow the acquisition of high-fidelity 3D digital r
 eplicas of the as-is status. However\, the output of such systems does not
  provide information on the spatial components\, attributes and in-between
  relationships\, thus cannot support downstream tasks (e.g.\, construction
  progress monitoring\, maintenance activities\, etc.). In this talk I will
  describe recent work on the automated extraction and knowledge-based repr
 esentation of this information from visual data using Machine Vision and A
 I\, as well as how it improves existing processes and enables novel workfl
 ows.\n\nIro Armeni is a PhD candidate at Stanford University\, conducting 
 interdisciplinary research between Civil Engineering and Machine Vision. H
 er area of focus is on automated semantic and operational understanding of
  buildings throughout their life cycle using visual data. Prior to enrolli
 ng in PhD program\, Iro received an MEng in Architecture and Digital Desig
 n (University of Tokyo-2011)\, an MSc in Computer Science (Ionian Universi
 ty-2013)\, and a Diploma in Architectural Engineering (National Technical 
 University of Athens-2009). She is the recipient of the Google PhD Fellows
 hip on Machine Perception and the Japanese Government (MEXT) scholarship\,
  among other awards. She is also a co-instructor in the class "AI applicat
 ions in the AEC industry" at Stanford University. Iro has worked as an arc
 hitect and consultant for both the private and public sector.
LOCATION:GC G1 515 https://plan.epfl.ch/?room=GCG1515
STATUS:CONFIRMED
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