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dc.contributor.authorWilko Sommer, Lars
dc.date.accessioned2022-02-28T14:31:05Z
dc.date.available2022-02-28T14:31:05Z
dc.date.issued2022
dc.identifierONIX_20220228_9783731511137_3
dc.identifier.issn1863-6489
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/53149
dc.description.abstractThis book proposes a novel deep learning based detection method, focusing on vehicle detection in aerial imagery recorded in top view. The base detection framework is extended by two novel components to improve the detection accuracy by enhancing the contextual and semantical content of the employed feature representation. To reduce the inference time, a lightweight CNN architecture is proposed as base architecture and a novel module that restricts the search area is introduced.
dc.languageEnglish
dc.relation.ispartofseriesKarlsruher Schriften zur Anthropomatik
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientistsen_US
dc.subject.otherObjektdetektion
dc.subject.otherNeuronale Netze
dc.subject.otherLuftbilddaten
dc.subject.otherObject Detection
dc.subject.otherDeep Learning
dc.subject.otherAerial Imagery
dc.titleDeep Learning based Vehicle Detection in Aerial Imagery
dc.typebook
oapen.identifier.doi10.5445/KSP/1000135415
oapen.relation.isPublishedBy44e29711-8d53-496b-85cc-3d10c9469be9
oapen.relation.isbn9783731511137
oapen.imprintKIT Scientific Publishing
oapen.series.number52
oapen.pages276
oapen.place.publicationKarlsruhe


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