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Ship Detection in Radar Image Series Based on the Long Short-Term Memory Network

  • Beihang University

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

Abstract

Ship detection is one of the important ocean applications of radar images. However, researches for ship detection in low-resolution images are relatively scarce. To improve the ship detection performance in low-resolution conditions, the paper adopts the range-Doppler (RD) images and takes advantage of the multi-frame information with the long short-term memory (LSTM) network. In this paper, the interpolation method and the LSTM method are proposed, which have the advantages of speed and precision respectively and show strong anti-interference ability.

Original languageEnglish
Title of host publication2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1229-1232
Number of pages4
ISBN (Electronic)9781728163741
DOIs
StatePublished - 26 Sep 2020
Event2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Virtual, Waikoloa, United States
Duration: 26 Sep 20202 Oct 2020

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Country/TerritoryUnited States
CityVirtual, Waikoloa
Period26/09/202/10/20

Keywords

  • LSTM
  • Ship detection
  • jamming recognition
  • low-resolution radar

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