Closed Loop Perception for Resource Efficient Autonomous Systems

#Deep #Learning #Computer #Vision #Autonomous #Systems
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Autonomous Systems such as Autonomous Vehicles (AV), robots and drones are being developed for large scale deployments in real world applications such as transportation, agriculture, defense, urban planning etc. To operate safely in such diverse and dynamic scenarios, the perception engine within these systems must be capable of adapting to the dynamic real-time constraints such as latency and energy consumption. This adaptability is not present in the modern perception systems as they are open-loop by design and therefore neither aware nor capable of reacting to the dynamics of a real-world scenario. In this talk we will explore the Closed Loop Perception that interprets the perception process in modern autonomous systems as a control system. The Closed Loop Perception System can introspect and adapt to the real-time requirements of an Autonomous System operating in the wild.



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  • Date: 24 Mar 2022
  • Time: 05:30 PM to 06:30 PM
  • All times are (GMT-06:00) US/Central
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  • Starts 03 March 2022 09:43 PM
  • Ends 24 March 2022 05:30 PM
  • All times are (GMT-06:00) US/Central
  • No Admission Charge


  Speakers

Kruttidipta Samal Kruttidipta Samal

Biography:

Kruttidipta Samal is a PostDoc in the School of Computing at University of Nebraska – Lincoln. He finished his PhD in ECE from Georgia Tech in 2022 and MS from Georgia Tech in 2016. Prior to joining the PhD program, he was with the End user Computing Team, VMWare USA. His research interests include Deep Learning, Computer Vision, Resource Efficient Perception System and AgTech.