A Deep Learning-based Jellyfish Distribution Monitoring System using an Unmanned Aerial Vehicle

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 275
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKoo, Jung Moko
dc.contributor.authorKim, Han Guenko
dc.contributor.authorKim, Dong Hoonko
dc.contributor.authorJung, Sung Wookko
dc.contributor.authorMyung, Hyunko
dc.date.accessioned2016-04-18T04:59:08Z-
dc.date.available2016-04-18T04:59:08Z-
dc.date.created2015-11-21-
dc.date.created2015-11-21-
dc.date.issued2015-09-30-
dc.identifier.citationInt’l Conf. on Intelligent Robots and Systems (IROS)-
dc.identifier.urihttp://hdl.handle.net/10203/204327-
dc.languageEnglish-
dc.publisherIEEE Robotics and Automation Society (RAS)-
dc.titleA Deep Learning-based Jellyfish Distribution Monitoring System using an Unmanned Aerial Vehicle-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameInt’l Conf. on Intelligent Robots and Systems (IROS)-
dc.identifier.conferencecountryGE-
dc.identifier.conferencelocationCongress Center Hamburg-
dc.contributor.localauthorMyung, Hyun-
dc.contributor.nonIdAuthorKoo, Jung Mo-
dc.contributor.nonIdAuthorJung, Sung Wook-
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0