LEADER 00918nam0-2200277---450- 001 990008556870403321 005 20090406151927.0 035 $a000855687 035 $aFED01000855687 035 $a(Aleph)000855687FED01 035 $a000855687 100 $a20070928d1973----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $a--------001yy 200 1 $aLicences de brevet et droit communautaire de la concurrence$esupplément au chapitre 'Concurrence' du 'Dictionnaire du Marché commun' [de] Gide, Loyrette, Nouel$fpar Krzysztof Nowacki 210 $aParis$cJuridictionnaires Joly$d1973 215 $aXVI, 201 p.$d25 cm 700 1$aNowacki,$bKrzysztof$0314414 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990008556870403321 952 $aDI 8/287$b4552$fDEC 959 $aDEC 996 $aLicences de brevet et droit communautaire de la concurrence$9709128 997 $aUNINA LEADER 01429nam 2200361 450 001 9910629576503321 005 20230224125129.0 035 $a(CKB)5720000000108119 035 $a(NjHacI)995720000000108119 035 $a(EXLCZ)995720000000108119 100 $a20230224d2022 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSelf-supervised learning for visual obstacle avoidance $etechnical report /$fTom van Dijk 210 1$aDelft :$cTU Delft OPEN Publishing,$d[2022] 210 4$d©2022 215 $a1 online resource (48 pages) 311 $a94-6366-509-9 330 $aWith a growing number of drones, the risk of collision with other air traffic or fixed obstacles increases. New safety measures are required to keep the operation of Unmanned Aerial Vehicles (UAVs) safe. One of these measures is the use of a Collision Avoidance System (CAS), a system that helps the drone autonomously detect and avoid obstacles. 517 $aSelf-Supervised Learning for Visual Obstacle Avoidance 606 $aDrone aircraft 615 0$aDrone aircraft. 676 $a623.7469 700 $aDijk$b Tom van$01281145 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910629576503321 996 $aSelf-supervised learning for visual obstacle avoidance$93018221 997 $aUNINA LEADER 01785oam 2200541zu 450 001 9911007034203321 005 20210807002107.0 010 $a0-89871-832-5 035 $a(CKB)3170000000010428 035 $a(SSID)ssj0000671203 035 $a(PQKBManifestationID)11409082 035 $a(PQKBTitleCode)TC0000671203 035 $a(PQKBWorkID)10613687 035 $a(PQKB)10189256 035 $a(WaSeSS)Innodata00029722 035 $a(PPN)190779268 035 $a(EXLCZ)993170000000010428 100 $a20160829d2001 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMathematical methods in image reconstruction 210 31$a[Place of publication not identified]$cSociety for Industrial and Applied Mathematics$d2001 215 $a1 online resource (230 p.) 225 0 $aSIAM monographs on mathematical modeling and computation Mathematical methods in image reconstruction 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-61344-321-8 311 $a0-89871-622-5 320 $aIncludes bibliographical references and index. 606 $aImage processing$vCongresses 606 $aEngineering & Applied Sciences$2HILCC 606 $aApplied Physics$2HILCC 615 0$aImage processing 615 7$aEngineering & Applied Sciences 615 7$aApplied Physics 676 $a621.36/7 700 $aNatterer$b F$g(Frank),$f1941-$060213 702 $aNatterer$b F 702 $aWèubbeling$b Frank 702 $aWübbeling$b Frank 712 02$aSociety for Industrial and Applied Mathematics. 801 0$bPQKB 906 $aBOOK 912 $a9911007034203321 996 $aMathematical methods in image reconstruction$94391122 997 $aUNINA