A deep learning approach for dynamic object understanding using SIFT

Yuan Tsung Chang, Timothy K. Shih

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Deep learning is a method that is very commonly used in image recognition. We use the SIFT method to extract feature points, so that the machine can detect the objects in the motion images and they can be integrated into the operation of the robot arm to judge and capture specific objects. This method is also used to detect whether the parameters of the object meet the predetermined values. It will provide a warning if the predetermined values are not met. This can be used to identify the good and defective products on the production line. In the CNN database we have trained more than 30,000 images and improved the last step of SIFT algorithm to demonstrate that our new method can achieve better accuracy.

Original languageEnglish
Title of host publicationProceedings - 2019 12th International Conference on Ubi-Media Computing, Ubi-Media 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages130-134
Number of pages5
ISBN (Electronic)9781728128207
DOIs
StatePublished - Aug 2019
Event12th International Conference on Ubi-Media Computing, Ubi-Media 2019 - Bali, Indonesia
Duration: 6 Aug 20199 Aug 2019

Publication series

NameProceedings - 2019 12th International Conference on Ubi-Media Computing, Ubi-Media 2019

Conference

Conference12th International Conference on Ubi-Media Computing, Ubi-Media 2019
Country/TerritoryIndonesia
CityBali
Period6/08/199/08/19

Keywords

  • CNN
  • Deep learning
  • Library
  • SIFT

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