CSK-Detector: Commonsense in object detection

Irina Chernyavsky, Aparna S. Varde, Simon Razniewski

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

1 Scopus citations

Abstract

We propose an approach CSK-Detector for object detection and image categorization, well-suited for big data, by transferring commonsense knowledge from a knowledge base, augmented with premises and quantifiers. It is implemented for domestic robotics, especially with the motivation that next-generation and multipurpose domestic robots should be able to seamlessly discern environments for specific tasks without prior annotation of excessive images. CSK-Detector is evaluated on real data, yielding better results than deep learning without commonsense, while also providing an explainable approach. It broadly impacts human-robot collaboration and smart living.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
EditorsShusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6609-6612
Number of pages4
ISBN (Electronic)9781665480451
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Big Data, Big Data 2022 - Osaka, Japan
Duration: 17 Dec 202220 Dec 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

Conference

Conference2022 IEEE International Conference on Big Data, Big Data 2022
Country/TerritoryJapan
CityOsaka
Period17/12/2220/12/22

Keywords

  • Big data
  • commonsense knowledge
  • domestic robotics
  • explainable AI
  • image categorization
  • smart living

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