Publicación:
Real-Time Detection Method of Persistent Objects in Radar Imagery with Deep Learning

dc.contributor.author Martinez R.G. es_PE
dc.contributor.author Vera J.M. es_PE
dc.contributor.author Arrese C.C. es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2020
dc.description.abstract Persistent object detection in radar imagery becomes harder if the results are expected before the next image arrives to the digitizer card. This requires a clear commitment between the hit rate, the false contact rate and a time restriction in order to get real-Time results taking one full revolution of the radar as the basic unit. The conventional algorithms use CFAR techniques and obtain acceptable results, but with a high false contact rate, especially in near-shore radar imagery, which contain ground clutter portions of the images. This work presents the first results of the analysis to the solutions to this problem by applying Deep Learning. This research proposes the use of convolutional neural networks Faster R-CNN on radar imagery. The developed methods are applied using a methodology. The purpose of this research is to provide methods and techniques to improve the detection of persistent objects, thus having a positive impact in the maritime control and surveillance operations. © 2020 IEEE.
dc.description.sponsorship Fondo Nacional de Desarrollo Científico y Tecnológico - Fondecyt
dc.identifier.doi https://doi.org/10.1109/EIRCON51178.2020.9254021
dc.identifier.scopus 2-s2.0-85097841266
dc.identifier.uri https://hdl.handle.net/20.500.12390/2474
dc.language.iso eng
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof Proceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
dc.rights info:eu-repo/semantics/openAccess
dc.subject Radar images
dc.subject Faster R-CNN es_PE
dc.subject Persistent objects es_PE
dc.subject.ocde http://purl.org/pe-repo/ocde/ford#2.02.03
dc.title Real-Time Detection Method of Persistent Objects in Radar Imagery with Deep Learning
dc.type info:eu-repo/semantics/article
dspace.entity.type Publication
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oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
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