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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:MS Thesis Final Exam - Cheng-Che Shih
X-WR-TIMEZONE:Pacific Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260517T021143Z
UID:tag:localist.com\,2008:EventInstance_41712992673615
DTSTART:20221205T180000Z
DTEND:20221205T200000Z
DESCRIPTION:A people tracking and counting system based on the low-cost mil
 limeter wave sensor and 3-dimensional Convolutional Neural Networks (3DCNN
 )\n\nMillimeter wave sensors nowadays play a significant role in the appli
 cations of counting and tracking objects due to their great power efficien
 cy and detection performance. Moreover\, the technology of object detectio
 n has recently obtained important attention because the technologies are b
 eneficial to a variety of fields such as security and energy-efficient app
 lications. In this thesis\, we propose a low-cost\, and low-complexity but
  highly accurate method to count and track objects in a small indoor space
 . The proposed system is developed by applying the low-cost mm-wave radar 
 from Texas Instruments\, 3-dimensional RF images which include coordinate 
 and Doppler velocity information\, and 3-dimensional Convolutional Neural 
 Networks. To be more specific\, the proposed method is able to achieve acc
 uracies as high as 95%\, operating at 10 frames per second\, to distinguis
 h 4 different moving objects in a small indoor environment.\n\nMAJOR ADVIS
 OR: Thinh Nguyen\nCOMMITTEE: Jinsub Kim \nCOMMITTEE: Bella Bose\nCOMMITTEE
 : Raviv Raich\nGCR: Roberto Albertani
GEO:44.567164;-123.278692
LOCATION:Kelley Engineering Center\, 1126
SUMMARY:MS Thesis Final Exam - Cheng-Che Shih
URL;VALUE=URI:https://events.oregonstate.edu/event/ms_thesis_final_exam_-_c
 heng-che_shih
CATEGORIES:Lecture or Presentation
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