0536724 20240103225020.720201229235959.9 9 s. P cav_un_epca*05367391613-0073AchenCEUR-WS.org2020 Computer Vision Object Detection Machine Learning cav_un_auth*0293261 Zita Aleš UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI K Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0401593 Picek L. CZ cav_un_auth*0208239 Říha A. CZ http://library.utia.cas.cz/separaty/2020/ZOI/zita-0536724.pdf LO1506 GA MŠk CZ cav_un_auth*0319164 Transcription of User Interface (UI) elements hand drawings to the computer code is a tedious and repetitive task. Therefore, a need arose to create a system capable of automating such process. This paper describes a deep learning-based method for hand-drawn user interface elements detection and localization. The proposed method scored 1st place in the ImageCLEFdrawnUI competition while achieving an overall precision of 0.9708. The final method is based on Faster R-CNN object detector framework with ResNet-50 backbone architecture trained with advanced regularization techniques. The code has been made available at: https://github.com/picekl/ImageCLEF2020-DrawnUI. cav_un_auth*0401575 CLEF 2020 20200922 20200925 Thessaloniki GR JD 20000 20200 20204 2021 3 PR RVO:67985556 http://hdl.handle.net/11104/0314461 1 cav_un_auth*0300913 Západočeská univerzita Plzeň ZUČ CZ cav_un_auth*0401576 ČVUT Fakulta informačních technologií ČVUT FIT CZ S 82 0.166 Q3 2020 SCOPUS PUBMED WOS cav_un_epca*0536739 CEUR Workshop Proceedings : Volume 2696. Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum 1613-0073 Achen CEUR-WS.org 2020