{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T06:15:53Z","timestamp":1762409753668,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030504359"},{"type":"electronic","value":"9783030504366"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-50436-6_24","type":"book-chapter","created":{"date-parts":[[2020,6,19]],"date-time":"2020-06-19T19:03:44Z","timestamp":1592593424000},"page":"326-339","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Combined Metrics for Quality Assessment of 3D Printed Surfaces for Aesthetic Purposes: Towards Higher Accordance with Subjective Evaluations"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3315-1281","authenticated-orcid":false,"given":"Jaros\u0142aw","family":"Fastowicz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2554-7582","authenticated-orcid":false,"given":"Piotr","family":"Lech","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6721-3241","authenticated-orcid":false,"given":"Krzysztof","family":"Okarma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,6,15]]},"reference":[{"issue":"3","key":"24_CR1","doi-asserted-by":"publisher","first-page":"1260","DOI":"10.1021\/acs.est.5b04983","volume":"50","author":"P Azimi","year":"2016","unstructured":"Azimi, P., Zhao, D., Pouzet, C., Crain, N.E., Stephens, B.: Emissions of ultrafine particles and volatile organic compounds from commercially available desktop three-dimensional printers with multiple filaments. Environ. Sci. Technol. 50(3), 1260\u20131268 (2016)","journal-title":"Environ. Sci. Technol."},{"issue":"12","key":"24_CR2","doi-asserted-by":"publisher","first-page":"993","DOI":"10.1007\/s10762-014-0113-9","volume":"35","author":"SF Busch","year":"2014","unstructured":"Busch, S.F., Weidenbach, M., Fey, M., Sch\u00e4fer, F., Probst, T., Koch, M.: Optical properties of 3D printable plastics in the THz regime and their application for 3D printed THz optics. J. Infrared Millimeter Terahertz Waves 35(12), 993\u2013997 (2014). https:\/\/doi.org\/10.1007\/s10762-014-0113-9","journal-title":"J. Infrared Millimeter Terahertz Waves"},{"key":"24_CR3","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1016\/j.promfg.2015.09.051","volume":"1","author":"V Chauhan","year":"2015","unstructured":"Chauhan, V., Surgenor, B.: A comparative study of machine vision based methods for fault detection in an automated assembly machine. Proc. Manuf. 1, 416\u2013428 (2015). https:\/\/doi.org\/10.1016\/j.promfg.2015.09.051","journal-title":"Proc. Manuf."},{"issue":"9","key":"24_CR4","doi-asserted-by":"publisher","first-page":"2491","DOI":"10.1007\/s00170-016-9581-5","volume":"90","author":"V Chauhan","year":"2016","unstructured":"Chauhan, V., Surgenor, B.: Fault detection and classification in automated assembly machines using machine vision. Int. J. Adv. Manuf. Technol. 90(9), 2491\u20132512 (2016). https:\/\/doi.org\/10.1007\/s00170-016-9581-5","journal-title":"Int. J. Adv. Manuf. Technol."},{"issue":"1","key":"24_CR5","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/TASE.2007.912058","volume":"5","author":"Y Cheng","year":"2008","unstructured":"Cheng, Y., Jafari, M.A.: Vision-based online process control in manufacturing applications. IEEE Trans. Autom. Sci. Eng. 5(1), 140\u2013153 (2008). https:\/\/doi.org\/10.1109\/TASE.2007.912058","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"24_CR6","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1016\/j.promfg.2018.07.111","volume":"26","author":"U Delli","year":"2018","unstructured":"Delli, U., Chang, S.: Automated process monitoring in 3D printing using supervised machine learning. Proc. Manuf. 26, 865\u2013870 (2018). https:\/\/doi.org\/10.1016\/j.promfg.2018.07.111","journal-title":"Proc. Manuf."},{"key":"24_CR7","doi-asserted-by":"publisher","unstructured":"Fang, T., Jafari, M.A., Bakhadyrov, I., Safari, A., Danforth, S., Langrana, N.: Online defect detection in layered manufacturing using process signature. In: Proceedings of IEEE International Conference on Systems, Man and Cybernetics, San Diego, CA, USA, vol. 5, pp. 4373\u20134378 (1998). https:\/\/doi.org\/10.1109\/ICSMC.1998.727536","DOI":"10.1109\/ICSMC.1998.727536"},{"issue":"2","key":"24_CR8","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s00138-002-0074-1","volume":"15","author":"T Fang","year":"2003","unstructured":"Fang, T., Jafari, M.A., Danforth, S.C., Safari, A.: Signature analysis and defect detection in layered manufacturing of ceramic sensors and actuators. Mach. Vis. Appl. 15(2), 63\u201375 (2003). https:\/\/doi.org\/10.1007\/s00138-002-0074-1","journal-title":"Mach. Vis. Appl."},{"issue":"1","key":"24_CR9","doi-asserted-by":"publisher","first-page":"97","DOI":"10.3390\/e21010097","volume":"21","author":"J Fastowicz","year":"2019","unstructured":"Fastowicz, J., Grudzi\u0144ski, M., Tec\u0142aw, M., Okarma, K.: Objective 3D printed surface quality assessment based on entropy of depth maps. Entropy 21(1), 97 (2019). https:\/\/doi.org\/10.3390\/e21010097","journal-title":"Entropy"},{"key":"24_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/978-3-319-46418-3_2","volume-title":"Computer Vision and Graphics","author":"J Fastowicz","year":"2016","unstructured":"Fastowicz, J., Okarma, K.: Texture based quality assessment of 3D prints for different lighting conditions. In: Chmielewski, L.J., Datta, A., Kozera, R., Wojciechowski, K. (eds.) ICCVG 2016. LNCS, vol. 9972, pp. 17\u201328. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46418-3_2"},{"key":"24_CR11","unstructured":"Fastowicz, J., Okarma, K.: Quality assessment of photographed 3D printed flat surfaces using Hough transform and histogram equalization. J. Univ. Compu. Sci. 25(6), 701\u2013717 (2019). http:\/\/www.jucs.org\/jucs_25_6\/quality_assessment_of_photographed"},{"key":"24_CR12","doi-asserted-by":"publisher","first-page":"041407","DOI":"10.1117\/1.OE.57.4.041407","volume":"57","author":"MR Gardner","year":"2018","unstructured":"Gardner, M.R., et al.: In situ process monitoring in selective laser sintering using optical coherence tomography. Opt. Eng. 57, 041407 (2018). https:\/\/doi.org\/10.1117\/1.OE.57.4.041407","journal-title":"Opt. Eng."},{"key":"24_CR13","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.addma.2016.10.004","volume":"13","author":"M Hirsch","year":"2017","unstructured":"Hirsch, M., et al.: Assessing the capability of in-situ nondestructive analysis during layer based additive manufacture. Addit. Manuf. 13, 135\u2013142 (2017). https:\/\/doi.org\/10.1016\/j.addma.2016.10.004","journal-title":"Addit. Manuf."},{"key":"24_CR14","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.addma.2017.08.003","volume":"17","author":"O Holzmond","year":"2017","unstructured":"Holzmond, O., Li, X.: In situ real time defect detection of 3D printed parts. Addit. Manuf. 17, 135\u2013142 (2017). https:\/\/doi.org\/10.1016\/j.addma.2017.08.003","journal-title":"Addit. Manuf."},{"issue":"11","key":"24_CR15","doi-asserted-by":"publisher","first-page":"260-1","DOI":"10.2352\/ISSN.2470-1173.2019.11.IPAS-260","volume":"2019","author":"O Ieremeiev","year":"2019","unstructured":"Ieremeiev, O., Lukin, V., Ponomarenko, N., Egiazarian, K.: Combined no-reference IQA metric and its performance analysis. Electron. Imaging 2019(11), 260-1\u2013260-7 (2019). https:\/\/doi.org\/10.2352\/ISSN.2470-1173.2019.11.IPAS-260","journal-title":"Electron. Imaging"},{"issue":"3","key":"24_CR16","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1108\/RPJ-03-2017-0048","volume":"24","author":"H Kim","year":"2018","unstructured":"Kim, H., Lin, Y., Tseng, T.L.B.: A review on quality control in additive manufacturing. Rapid Prototyping J. 24(3), 645\u2013669 (2018). https:\/\/doi.org\/10.1108\/RPJ-03-2017-0048","journal-title":"Rapid Prototyping J."},{"key":"24_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-030-00692-1_18","volume-title":"Computer Vision and Graphics","author":"P Lech","year":"2018","unstructured":"Lech, P., Fastowicz, J., Okarma, K.: Quality evaluation of 3D printed surfaces based on HOG features. In: Chmielewski, L.J., Kozera, R., Or\u0142owski, A., Wojciechowski, K., Bruckstein, A.M., Petkov, N. (eds.) ICCVG 2018. LNCS, vol. 11114, pp. 199\u2013208. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00692-1_18"},{"key":"24_CR18","doi-asserted-by":"publisher","unstructured":"Makagonov, N.G., Blinova, E.M., Bezukladnikov, I.I.: Development of visual inspection systems for 3D printing. In: 2017 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus, pp. 1463\u20131465, February 2017. https:\/\/doi.org\/10.1109\/EIConRus.2017.7910849","DOI":"10.1109\/EIConRus.2017.7910849"},{"key":"24_CR19","doi-asserted-by":"publisher","unstructured":"Okarma, K., Fastowicz, J.: No-reference quality assessment of 3D prints based on the GLCM analysis. In: Proceedings of the 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR, pp. 788\u2013793 (2016). https:\/\/doi.org\/10.1109\/MMAR.2016.7575237","DOI":"10.1109\/MMAR.2016.7575237"},{"key":"24_CR20","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1007\/978-3-642-13208-7_67","volume-title":"Artificial Intelligence and Soft Computing","author":"K Okarma","year":"2010","unstructured":"Okarma, K.: Combined full-reference image quality metric linearly correlated with subjective assessment. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010. LNCS (LNAI), vol. 6113, pp. 539\u2013546. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-13208-7_67"},{"issue":"5","key":"24_CR21","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/s10043-012-0055-1","volume":"19","author":"K Okarma","year":"2012","unstructured":"Okarma, K.: Combined image similarity index. Opt. Rev. 19(5), 349\u2013354 (2012). https:\/\/doi.org\/10.1007\/s10043-012-0055-1","journal-title":"Opt. Rev."},{"issue":"6","key":"24_CR22","doi-asserted-by":"publisher","first-page":"128","DOI":"10.5755\/j01.eee.20.6.7284","volume":"20","author":"K Okarma","year":"2014","unstructured":"Okarma, K.: Quality assessment of images with multiple distortions using combined metrics. Elektronika Ir Elektrotechnika 20(6), 128\u2013131 (2014). https:\/\/doi.org\/10.5755\/j01.eee.20.6.7284","journal-title":"Elektronika Ir Elektrotechnika"},{"key":"24_CR23","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1007\/978-3-319-59162-9_32","volume-title":"Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017","author":"K Okarma","year":"2018","unstructured":"Okarma, K., Fastowicz, J.: Color independent quality assessment of 3D printed surfaces based on image entropy. In: Kurzynski, M., Wozniak, M., Burduk, R. (eds.) CORES 2017. AISC, vol. 578, pp. 308\u2013315. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-59162-9_32"},{"issue":"5","key":"24_CR24","doi-asserted-by":"publisher","first-page":"57","DOI":"10.5755\/j01.eie.25.5.24357","volume":"25","author":"K Okarma","year":"2019","unstructured":"Okarma, K., Fastowicz, J.: Adaptation of full-reference image quality assessment methods for automatic visual evaluation of the surface quality of 3D prints. Elektronika Ir Elektrotechnika 25(5), 57\u201362 (2019). https:\/\/doi.org\/10.5755\/j01.eie.25.5.24357","journal-title":"Elektronika Ir Elektrotechnika"},{"key":"24_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"790","DOI":"10.1007\/978-3-540-69384-0_84","volume-title":"Computational Science \u2013 ICCS 2008","author":"K Okarma","year":"2008","unstructured":"Okarma, K., Lech, P.: Monte Carlo based algorithm for fast preliminary video analysis. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008. LNCS, vol. 5101, pp. 790\u2013799. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-69384-0_84"},{"issue":"1","key":"24_CR26","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1109\/LSP.2015.2500819","volume":"23","author":"M Oszust","year":"2016","unstructured":"Oszust, M.: Decision fusion for image quality assessment using an optimization approach. IEEE Signal Process. Lett. 23(1), 65\u201369 (2016). https:\/\/doi.org\/10.1109\/LSP.2015.2500819","journal-title":"IEEE Signal Process. Lett."},{"key":"24_CR27","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.addma.2017.11.009","volume":"19","author":"L Scime","year":"2018","unstructured":"Scime, L., Beuth, J.: Anomaly detection and classification in a laser powder bed additive manufacturing process using a trained computer vision algorithm. Addit. Manuf. 19, 114\u2013126 (2018). https:\/\/doi.org\/10.1016\/j.addma.2017.11.009","journal-title":"Addit. Manuf."},{"issue":"4","key":"24_CR28","doi-asserted-by":"publisher","first-page":"129:1","DOI":"10.1145\/2766962","volume":"34","author":"P Sitthi-Amorn","year":"2015","unstructured":"Sitthi-Amorn, P., et al.: MultiFab: a machine vision assisted platform for multi-material 3D printing. ACM Trans. Graph. 34(4), 129:1\u2013129:11 (2015). https:\/\/doi.org\/10.1145\/2766962","journal-title":"ACM Trans. Graph."},{"key":"24_CR29","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.atmosenv.2013.06.050","volume":"79","author":"B Stephens","year":"2013","unstructured":"Stephens, B., Azimi, P., Orch, Z.E., Ramos, T.: Ultrafine particle emissions from desktop 3D printers. Atmos. Environ. 79, 334\u2013339 (2013)","journal-title":"Atmos. Environ."},{"issue":"2","key":"24_CR30","doi-asserted-by":"publisher","first-page":"55","DOI":"10.3390\/machines3020055","volume":"3","author":"J Straub","year":"2015","unstructured":"Straub, J.: Initial work on the characterization of additive manufacturing (3D printing) using software image analysis. Machines 3(2), 55\u201371 (2015). https:\/\/doi.org\/10.3390\/machines3020055","journal-title":"Machines"},{"key":"24_CR31","doi-asserted-by":"crossref","unstructured":"Tourloukis, G., Stoyanov, S., Tilford, T., Bailey, C.: Data driven approach to quality assessment of 3D printed electronic products. In: Proceedings of the 38th International Spring Seminar on Electronics Technology, ISSE, pp. 300\u2013305 (2015)","DOI":"10.1109\/ISSE.2015.7248010"},{"issue":"4","key":"24_CR32","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004). https:\/\/doi.org\/10.1109\/TIP.2003.819861","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"24_CR33","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1108\/RPJ-02-2017-0031","volume":"24","author":"H Wu","year":"2018","unstructured":"Wu, H., Chen, T.: Quality control issues in 3D-printing manufacturing: a review. Rapid Prototyping J. 24(3), 607\u2013614 (2018). https:\/\/doi.org\/10.1108\/RPJ-02-2017-0031","journal-title":"Rapid Prototyping J."},{"issue":"7","key":"24_CR34","doi-asserted-by":"publisher","first-page":"1872","DOI":"10.1007\/s11837-016-1937-7","volume":"68","author":"SE Zeltmann","year":"2016","unstructured":"Zeltmann, S.E., Gupta, N., Tsoutsos, N.G., Maniatakos, M., Rajendran, J., Karri, R.: Manufacturing and security challenges in 3D printing. JOM 68(7), 1872\u20131881 (2016). https:\/\/doi.org\/10.1007\/s11837-016-1937-7","journal-title":"JOM"},{"issue":"8","key":"24_CR35","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"Zhang, L., Zhang, L., Mou, X., Zhang, D.: FSIM: A feature similarity index for image quality assessment. IEEE Trans. Image Process. 20(8), 2378\u20132386 (2011). https:\/\/doi.org\/10.1109\/TIP.2011.2109730","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"24_CR36","doi-asserted-by":"publisher","first-page":"035011","DOI":"10.1088\/1361-6501\/ab524b","volume":"31","author":"X Zhao","year":"2019","unstructured":"Zhao, X., Lian, Q., He, Z., Zhang, S.: Region-based online flaw detection of 3D printing via fringe projection. Meas. Sci. Technol. 31(3), 035011 (2019). https:\/\/doi.org\/10.1088\/1361-6501\/ab524b","journal-title":"Meas. Sci. Technol."}],"container-title":["Lecture Notes in Computer Science","Computational Science \u2013 ICCS 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-50436-6_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T23:04:26Z","timestamp":1718751866000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-50436-6_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030504359","9783030504366"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-50436-6_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"15 June 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 June 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccs-computsci2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iccs-meeting.org\/iccs2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"230","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"98","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"248 workshop papers were selected from 489 submissions to the thematic tracks. The conference was canceled due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}