0546213 20220320214410.820211005235959.9 10.1007/978-3-030-88113-9_56 13 s. P cav_un_epca*0546212978-3-030-88113-91865-0929690-702ChamSpringer International Publishing2021WojtkiewiczKrystianTreurJanPimenidisEliasMaleszkaMarcin Remote sensing archeology underground heritage site recognition aerial image-based automated site detection cav_un_auth*0414746 Moudrá A. CZ cav_un_auth*0101093 Haindl Michal UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2021/RO/haindl-0546213.pdf GA19-12340S GA ČR CZ cav_un_auth*0376011 This paper introduces and compares three approaches for automatic archaeological heritage site detection hidden under soil cover from public aerial images. The methods use low quality public aerial RGB spectral data restricted by the land-use map to agricultural regions in the vegetation season to detect underground structure influencing plants growing on the surface soil layer. cav_un_auth*0414747 International Conference on Computational Collective Intelligence 2021 /13./ 20210929 20211001 Kallithea, Rhodes GR BD 20000 20200 20202 2022 2 PR RVO:67985556 http://hdl.handle.net/11104/0323756 cav_un_auth*0394151 Fakulta informačních technologií ČVUT FIT ČVUT CZ S 56 75 0.188 20.54 0.55 6188 Q3 2021 SCOPUS PUBMED WOS cav_un_epca*0546212 Advances in Computational Collective Intelligence Springer International Publishing 2021 Cham 690 702 978-3-030-88113-9 Communications in Computer and Information Science 1463 1865-0929 Wojtkiewicz Krystian 340 Treur Jan 340 Pimenidis Elias 340 Maleszka Marcin 340