Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12767
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dc.contributor.authorUzyıldırım, Furkan Erentr
dc.contributor.authorÖzuysal, Mustafatr
dc.date.accessioned2023-01-18T07:26:41Z-
dc.date.available2023-01-18T07:26:41Z-
dc.date.issued2022-
dc.identifier.urihttps://doi.org/10.1007/s11760-022-02463-1-
dc.identifier.urihttps://hdl.handle.net/11147/12767-
dc.description.abstractDue to increased potential applications of unmanned aerial vehicles over urban areas, algorithms for the safe landing of these devices have become more critical. One way to ensure a safe landing is to locate the ground plane regions of images captured by the device camera that are free of obstacles by deep semantic segmentation networks. In this paper, we study the performance of semantic segmentation networks trained for this purpose at a particular altitude and location. We show that a variation in altitude and location significantly decreases network performance. We then propose an approach to retrain the network using only a new set of images and without marking the ground regions in this novel training set. Our experiments show that we can convert a network’s operating range from low to high altitudes and vice versa by label-free retraining.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSignal Image and Video Processingen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectDeep learningen_US
dc.subjectGround plane segmentationen_US
dc.subjectSafe landing zoneen_US
dc.subjectUnmanned aerial vehiclesen_US
dc.titleLabel-free retraining for improved ground plane segmentationen_US
dc.typeArticleen_US
dc.authorid0000-0002-4219-3416en_US
dc.authorid0000-0003-0257-6882en_US
dc.institutionauthorUzyıldırım, Furkan Erentr
dc.institutionauthorÖzuysal, Mustafatr
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.wosWOS:000906136200002en_US
dc.identifier.scopus2-s2.0-85145187091en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıtr
dc.identifier.doi10.1007/s11760-022-02463-1-
dc.relation.issn1863-1703en_US
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextembargo_20250701-
crisitem.author.dept01.01. Units Affiliated to the Rectorate-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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