0536765 20240103225023.520201231235959.9 12 s. E cav_un_epca*05367391613-0073AchenCEUR-WS.org2020 Deep Learning Computer Vision Instance Segmentation cav_un_auth*0401593 Picek L. CZ cav_un_auth*0208239 Říha A. CZ cav_un_auth*0293261 Zita Aleš UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2020/ZOI/zita-0536765.pdf LO1506 GA MŠk CZ cav_un_auth*0319164 This article describes an automatic system for detection, classification and segmentation of individual coral substrates in underwater images. The proposed system achieved the best performances in both tasks of the second edition of the ImageCLEFcoral competition. Specifically, mean average precision with Intersection over Union (IoU) greater then 0.5 (mAP@0.5) of 0.582 in case of Coral reef image annotation and localisation, and mAP@0.5 of 0.678 in Coral reef image pixel-wise parsing. The system is based on Mask R-CNN object detection and instance segmentation framework boosted by advanced training strategies, pseudo-labeling, test-time augmentations, and Accumulated Gradient Normalisation. To support future research, 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/11104/0314743 1 cav_un_auth*0366658 Západočeská universita v Plzni ZČU CZ cav_un_auth*0394151 Fakulta informačních technologií ČVUT FIT ČVUT CZ S 83 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