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  • NVIDIA® Jetson™ Developer Challenge

This Challenge is completed

NVIDIA® Jetson™ Developer Challenge

NVIDIA® Jetson™ Developer Challenge
  • Winners announced
  • Winners announced
prize pool $42,789

SEE RESULTS

SEE RESULTS

Oct 23, 2017 - Feb 18, 2018 23:59 UTC
Voting: Feb 19 - Mar 04, 2018 23:59 UTC
  • Challenge outline
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NVIDIA® Jetson™ Developer Challenge
  • Challenge outline
  • Resources
  • Participants
  • Projects
  • FAQ
  • Results
  • Updates
  • Rules

RG

Richard Grundy

Added: Feb 19, 2018

Richard Grundy, Nicholas Dudfield, Scott Condron

TAGS

  1. Retail, RFID, Computer Vision, auto-training

TYPE OF PROJECT

System

WWW

flomio.com/smartcart

VOTES: 2 LIKES: 0

TrackPak

  • play
  • TrackPak

    Project description

    System is designed to use the Jetson TX2 platform as a sensor fusion center. Computer vision inference and RFID work collaboratively to train and improve models. Object classes are added as RFID tagged products are introduced into the store. Products are associated with object class data via RFID tags attached at initial phases of production. This approach allows for the system to phase in products in a AmazonGo-style retail environment. Over time the RFID tagging can be omitted once the CV inference performance is above the threshold approved by the merchant. 

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