{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T02:49:05Z","timestamp":1768704545977,"version":"3.49.0"},"reference-count":60,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"National Research, Development and Innovation Fund of Hungary, financed through the","award":["2019-1.3.1-KK"],"award-info":[{"award-number":["2019-1.3.1-KK"]}]},{"name":"Funding Scheme","award":["Project 2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["Project 2019-1.3.1-KK-2019-00007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tcyb.2023.3276485","type":"journal-article","created":{"date-parts":[[2023,6,7]],"date-time":"2023-06-07T17:36:30Z","timestamp":1686159390000},"page":"25-38","source":"Crossref","is-referenced-by-count":10,"title":["Increasing the Robustness of Deep Learning Models for Object Segmentation: A Framework for Blending Automatically Annotated Real and Synthetic Data"],"prefix":"10.1109","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2902-7253","authenticated-orcid":false,"given":"Art\u00far Istv\u00e1n","family":"K\u00e1roly","sequence":"first","affiliation":[{"name":"Antal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sebesty\u00e9n","family":"Tirczka","sequence":"additional","affiliation":[{"name":"Antal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5554-5452","authenticated-orcid":false,"given":"Huijun","family":"Gao","sequence":"additional","affiliation":[{"name":"Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2067-8578","authenticated-orcid":false,"given":"Imre J.","family":"Rudas","sequence":"additional","affiliation":[{"name":"Antal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2319-0551","authenticated-orcid":false,"given":"P\u00e9ter","family":"Galambos","sequence":"additional","affiliation":[{"name":"Antal Bejczy Center for Intelligent Robotics, Óbuda University, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364918770733"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9196887"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.01.012"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref5","first-page":"1","article-title":"How transferable are features in deep neural networks?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Yosinski"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00143"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202133"},{"key":"ref8","article-title":"Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection","author":"Levine","year":"2016","journal-title":"arXiv:1603.02199"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10055-019-00399-5"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8594495"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01073"},{"key":"ref13","article-title":"Deep object pose estimation for semantic robotic grasping of household objects","author":"Tremblay","year":"2018","journal-title":"arXiv:1809.10790"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/s21237901"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794443"},{"key":"ref16","article-title":"How much real data do we actually need: Analyzing object detection performance using synthetic and real data","author":"Nowruzi","year":"2019","journal-title":"arXiv:1907.07061"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"ref18","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-06381-7_1"},{"key":"ref20","first-page":"938","article-title":"SimNet: Enabling robust unknown object manipulation from pure synthetic data via stereo","volume-title":"Proc. Conf. Robot Learn.","author":"Kollar"},{"key":"ref21","article-title":"Learning keypoints from synthetic data for robotic cloth folding","author":"Lips","year":"2022","journal-title":"arXiv:2205.06714"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01437"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2017.XIII.058"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2021.103901"},{"key":"ref25","volume-title":"Blender\u2014A 3D Modelling and Rendering Package","year":"2018"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460887"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CASE49997.2022.9926640"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ETFA52439.2022.9921431"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3180403"},{"key":"ref30","article-title":"BlenderProc","author":"Denninger","year":"2019","journal-title":"arXiv:1911.01911"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00373"},{"key":"ref32","volume-title":"PyBullet, a python module for physics simulation for games, robotics and machine learning","author":"Coumans","year":"2019"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01258-8_23"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3149026"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8463191"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8461195"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197309"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58545-7_19"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.537"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.292"},{"key":"ref43","article-title":"What makes ImageNet good for transfer learning?","author":"Huh","year":"2016","journal-title":"arXiv:1608.08614"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref45","first-page":"1369","article-title":"The best of both modes: Separately leveraging RGB and depth for unseen object instance segmentation","volume-title":"Proc. Conf. Robot Learn.","author":"Xie"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2021.3060341"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2016.470"},{"key":"ref49","article-title":"Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?","author":"Johnson-Roberson","year":"2016","journal-title":"arXiv:1610.01983"},{"key":"ref50","article-title":"Continual learning from synthetic data for a humanoid exercise robot","author":"Duczek","year":"2021","journal-title":"arXiv:2102.10034"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00134"},{"key":"ref52","article-title":"Generative replay with feedback connections as a general strategy for continual learning","author":"Van de Ven","year":"2018","journal-title":"arXiv:1809.10635"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2015.2513408"},{"issue":"11","key":"ref54","first-page":"120","article-title":"The OpenCV library","volume":"25","author":"Bradski","year":"2000","journal-title":"Dr. Dobb\u2019s J. Softw. Tools"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.18260\/1-2--29663"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1093\/ons\/opab355"},{"key":"ref57","article-title":"Experience replay for continual learning","volume-title":"Advances in Neural Information Processing Systems","volume":"32","author":"Rolnick","year":"2019"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref59","volume-title":"Mask R-CNN for object detection and instance segmentation on keras and TensorFlow","author":"Abdulla","year":"2017"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/10367425\/10145828.pdf?arnumber=10145828","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T18:54:42Z","timestamp":1732906482000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10145828\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":60,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2023.3276485","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}