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A Survey on Autonomous Driving Datasets

  • Weiyu Liu
  • , Qian Dong
  • , Pengqi Wang
  • , Guang Yang
  • , Lingzhong Meng
  • , You Song
  • , Yuan Shi
  • , Yunzhi Xue
  • CAS - Institute of Software

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

Abstract

Currently the autonomous driving is one of the rapidly developing and widely concerned fields, which involves numerous artificial intelligence algorithms. Generally, these artificial intelligence algorithms require a large amount of diverse data for training and testing to ensure their performance in actual applications. In this paper, we introduce the types of data related to the autonomous driving, compare multiple datasets, and discusse the key issues in the process of dataset collection and generation.

Original languageEnglish
Title of host publicationProceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages399-407
Number of pages9
ISBN (Electronic)9781665443913
DOIs
StatePublished - 2021
Externally publishedYes
Event8th International Conference on Dependable Systems and Their Applications, DSA 2021 - Yinchuan, China
Duration: 11 Sep 202112 Sep 2021

Publication series

NameProceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021

Conference

Conference8th International Conference on Dependable Systems and Their Applications, DSA 2021
Country/TerritoryChina
CityYinchuan
Period11/09/2112/09/21

Keywords

  • Automatic labeling
  • Autonomous driving
  • Data type
  • Dataset
  • Domain adaptation

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