LEADER 01724nam  2200397z- 450 
001 9910548274803321
005 20231214133236.0
010   $a1000135415
035   $a(CKB)5670000000208450
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/78910
035   $a(EXLCZ)995670000000208450
100   $a20202203d2022      |y             0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aDeep Learning based Vehicle Detection in Aerial Imagery
210   $aKarlsruhe$cKIT Scientific Publishing$d2022
215   $a1 electronic resource (276 p.)
225 1 $aKarlsruher Schriften zur Anthropomatik
311   $a3-7315-1113-4 
330   $aThis 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.
606   $aMaths for computer scientists$2bicssc
610   $aObjektdetektion
610   $aNeuronale Netze
610   $aLuftbilddaten
610   $aObject Detection
610   $aDeep Learning
610   $aAerial Imagery
615  7$aMaths for computer scientists
700   $aWilko Sommer$b Lars$4auth$01327565
906   $aBOOK
912   $a9910548274803321
996   $aDeep Learning based Vehicle Detection in Aerial Imagery$93038022
997   $aUNINA