{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:39:01Z","timestamp":1783597141790,"version":"3.55.0"},"publisher-location":"Cham","reference-count":49,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030585853","type":"print"},{"value":"9783030585860","type":"electronic"}],"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\/978-3-030-58586-0_41","type":"book-chapter","created":{"date-parts":[[2020,11,29]],"date-time":"2020-11-29T17:02:42Z","timestamp":1606669362000},"page":"697-714","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":151,"title":["Fully Convolutional Networks for Continuous Sign Language Recognition"],"prefix":"10.1007","author":[{"given":"Ka Leong","family":"Cheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoyang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qifeng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-Wing","family":"Tai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,30]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Camgoz, N., Hadfield, S., Koller, O., Ney, H., Bowden, R.: Neural sign language translation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 7784\u20137793 (2018)","DOI":"10.1109\/CVPR.2018.00812"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Camgoz, N.C., Hadfield, S., Koller, O., Bowden, R.: Subunets: end-to-end hand shape and continuous sign language recognition. In: Proceedings of IEEE International Conference on Computer Vision, pp. 3075\u20133084 (2017)","DOI":"10.1109\/ICCV.2017.332"},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Cooper, H., Bowden, R.: Learning signs from subtitles: a weakly supervised approach to sign language recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2568\u20132574 (2009)","DOI":"10.1109\/CVPR.2009.5206647"},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Cui, R., Liu, H., Zhang, C.: Recurrent convolutional neural networks for continuous sign language recognition by staged optimization. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1610\u20131618 (2017)","DOI":"10.1109\/CVPR.2017.175"},{"key":"41_CR5","doi-asserted-by":"publisher","first-page":"1880","DOI":"10.1109\/TMM.2018.2889563","volume":"21","author":"R Cui","year":"2019","unstructured":"Cui, R., Liu, H., Zhang, C.: A deep neural framework for continuous sign language recognition by iterative training. IEEE Trans. Multimedia 21, 1880\u20131891 (2019)","journal-title":"IEEE Trans. Multimedia"},{"key":"41_CR6","doi-asserted-by":"crossref","unstructured":"Evangelidis, G.D., Singh, G., Horaud, R.: Continuous gesture recognition from articulated poses. In: Proceedings of European Conference on Computer Vision, pp. 595\u2013607 (2015)","DOI":"10.1007\/978-3-319-16178-5_42"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Fang, G., Gao, W.: A SRN\/HMM system for signer-independent continuous sign language recognition. In: Proceedings of IEEE International Conference on Automatic Face Gesture Recognition, pp. 312\u2013317 (2002)","DOI":"10.1007\/3-540-47873-6_8"},{"key":"41_CR8","doi-asserted-by":"crossref","unstructured":"Farhadi, A., Forsyth, D.: Aligning ASL for statistical translation using a discriminative word model. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1471\u20131476 (2006)","DOI":"10.1109\/CVPR.2006.51"},{"key":"41_CR9","doi-asserted-by":"crossref","unstructured":"Graves, A., Fern\u00e1ndez, S., Gomez, F., Schmidhuber, J.: Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks. In: Proceedings of International Conference on Machine Learning, pp. 369\u2013376 (2006)","DOI":"10.1145\/1143844.1143891"},{"key":"41_CR10","first-page":"1","volume":"14","author":"D Guo","year":"2017","unstructured":"Guo, D., Zhou, W., Li, H., Wang, M.: Online early-late fusion based on adaptive HMM for sign language recognition. ACM Trans. Multimedia Comput. Communi. Appl. 14, 1\u201318 (2017)","journal-title":"ACM Trans. Multimedia Comput. Communi. Appl."},{"key":"41_CR11","doi-asserted-by":"crossref","unstructured":"Guo, D., Zhou, W., Li, H., Wang, M.: Hierarchical LSTM for sign language translation. In: Proceedings of AAAI Conference on Artificial Intelligence, pp. 6845\u20136852 (2018)","DOI":"10.1609\/aaai.v32i1.12235"},{"key":"41_CR12","doi-asserted-by":"crossref","unstructured":"Guo, D., Zhou, W., Wang, M., Li, H.: Sign language recognition based on adaptive HMMs with data augmentation. In: Proceedings of IEEE International Conference on Image Processing, pp. 2876\u20132880 (2016)","DOI":"10.1109\/ICIP.2016.7532885"},{"key":"41_CR13","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1016\/j.patrec.2008.12.010","volume":"30","author":"J Han","year":"2009","unstructured":"Han, J., Awad, G., Sutherland, A.: Modelling and segmenting subunits for sign language recognition based on hand motion analysis. Pattern Recogn. Lett. 30, 623\u2013633 (2009)","journal-title":"Pattern Recogn. Lett."},{"key":"41_CR14","doi-asserted-by":"crossref","unstructured":"Huang, J., Zhou, W., Zhang, Q., Li, H., Li, W.: Video-based sign language recognition without temporal segmentation. In: Proceedings of AAAI Conference on Artificial Intelligence, pp. 2257\u20132264 (2018)","DOI":"10.1609\/aaai.v32i1.11903"},{"key":"41_CR15","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: Proceedings of International Conference on Machine Learning, pp. 448\u2013456 (2015)"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Kelly, D., McDonald, J., Markham, C.: Recognizing spatiotemporal gestures and movement epenthesis in sign language. In: Proceedings of IEEE International Conference on Image Processing and Machine Vision, pp. 145\u2013150 (2009)","DOI":"10.1109\/IMVIP.2009.33"},{"key":"41_CR17","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. CoRR preprint CoRR:1412.6980 (2014)"},{"key":"41_CR18","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.cviu.2015.09.013","volume":"141","author":"O Koller","year":"2015","unstructured":"Koller, O., Forster, J., Ney, H.: Continuous sign language recognition: towards large vocabulary statistical recognition systems handling multiple signers. Comput. Vis. Image Underst. 141, 108\u2013125 (2015)","journal-title":"Comput. Vis. Image Underst."},{"key":"41_CR19","doi-asserted-by":"crossref","unstructured":"Koller, O., Ney, H., Bowden, R.: Deep hand: how to train a CNN on 1 million hand images when your data is continuous and weakly labelled. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3793\u20133802 (2016)","DOI":"10.1109\/CVPR.2016.412"},{"key":"41_CR20","doi-asserted-by":"crossref","unstructured":"Koller, O., Zargaran, S., Ney, H.: Re-sign: re-aligned end-to-end sequence modelling with deep recurrent CNN-HMMs. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3416\u20133424 (2017)","DOI":"10.1109\/CVPR.2017.364"},{"key":"41_CR21","doi-asserted-by":"crossref","unstructured":"Koller, O., Zargaran, S., Ney, H., Bowden, R.: Deep sign: hybrid CNN-HMM for continuous sign language recognition. In: Proceedings of British Machine Vision Conference, pp. 136.1\u2013136.12 (2016)","DOI":"10.5244\/C.30.136"},{"key":"41_CR22","doi-asserted-by":"crossref","unstructured":"Liddell, S.K.: Grammar, Gestures, and Meaning in American Sign Language, pp. 52\u201353. Cambridge University Press, Cambridge (2003)","DOI":"10.1017\/CBO9780511615054"},{"key":"41_CR23","unstructured":"Liwicki, M., Graves, A., Bunke, H., Schmidhuber, J.: A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks. In: Proceedings of International Conference on Document Analysis and Recognition, pp. 367\u2013371 (2007)"},{"key":"41_CR24","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"41_CR25","doi-asserted-by":"crossref","unstructured":"Miao, Y., Gowayyed, M., Metze, F.: Eesen: end-to-end speech recognition using deep RNN models and WFST-based decoding. In: IEEE Conference on Automatic Speech Recognition and Understanding Workshops, pp. 167\u2013174 (2015)","DOI":"10.1109\/ASRU.2015.7404790"},{"key":"41_CR26","doi-asserted-by":"crossref","unstructured":"Molchanov, P., Yang, X., Gupta, S., Kim, K., Tyree, S., Kautz, J.: Online detection and classification of dynamic hand gestures with recurrent 3D convolutional neural networks. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 4207\u20134215 (2016)","DOI":"10.1109\/CVPR.2016.456"},{"key":"41_CR27","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1109\/TPAMI.2005.112","volume":"27","author":"S Ong","year":"2005","unstructured":"Ong, S., Ranganath, S.: Automatic sign language analysis: a survey and the future beyond lexical meaning. IEEE Trans. Pattern Anal. Mach. Intell. 27, 873\u201391 (2005)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"41_CR28","doi-asserted-by":"crossref","unstructured":"Pan, Y., Mei, T., Yao, T., Li, H., Rui, Y.: Jointly modeling embedding and translation to bridge video and language. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 4594\u20134602 (2015)","DOI":"10.1109\/CVPR.2016.497"},{"key":"41_CR29","doi-asserted-by":"crossref","unstructured":"Pitsikalis, V., Theodorakis, S., Vogler, C., Maragos, P.: Advances in phonetics-based sub-unit modeling for transcription alignment and sign language recognition. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 1\u20136 (2011)","DOI":"10.1109\/CVPRW.2011.5981681"},{"key":"41_CR30","doi-asserted-by":"crossref","unstructured":"Pu, J., Zhou, W., Li, H.: Dilated convolutional network with iterative optimization for continuous sign language recognition. In: Proceedings of International Joint Conference on Artificial Intelligence, pp. 885\u2013891 (2018)","DOI":"10.24963\/ijcai.2018\/123"},{"key":"41_CR31","doi-asserted-by":"crossref","unstructured":"Pu, J., Zhou, W., Li, H.: Iterative alignment network for continuous sign language recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 4165\u20134174 (2019)","DOI":"10.1109\/CVPR.2019.00429"},{"key":"41_CR32","doi-asserted-by":"crossref","unstructured":"Puigcerver, J.: Are multidimensional recurrent layers really necessary for handwritten text recognition? In: Proceedings of International Conference on Document Analysis and Recognition, pp. 67\u201372 (2017)","DOI":"10.1109\/ICDAR.2017.20"},{"key":"41_CR33","doi-asserted-by":"crossref","unstructured":"Sak, H., Senior, A., Rao, K., \u0130rsoy, O., Graves, A., Beaufays, F., Schalkwyk, J.: Learning acoustic frame labeling for speech recognition with recurrent neural networks. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4280\u20134284 (2015)","DOI":"10.1109\/ICASSP.2015.7178778"},{"key":"41_CR34","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1109\/TCYB.2013.2265337","volume":"43","author":"C Sun","year":"2013","unstructured":"Sun, C., Zhang, T., Bao, B.K., Xu, C., Mei, T.: Discriminative exemplar coding for sign language recognition with kinect. IEEE Trans. Cybern. 43, 1418\u20131428 (2013)","journal-title":"IEEE Trans. Cybern."},{"key":"41_CR35","doi-asserted-by":"crossref","unstructured":"Theodorakis, S., Katsamanis, A., Maragos, P.: Product-HMMs for automatic sign language recognition. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1601\u20131604 (2009)","DOI":"10.1109\/ICASSP.2009.4959905"},{"key":"41_CR36","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.patrec.2013.09.009","volume":"50","author":"AH Vela","year":"2014","unstructured":"Vela, A.H., et al.: Probability-based dynamic time warping and bag-of-visual-and-depth-words for human gesture recognition in RGB-D. Pattern Recogn. Lett. 50, 112\u2013121 (2014)","journal-title":"Pattern Recogn. Lett."},{"key":"41_CR37","doi-asserted-by":"crossref","unstructured":"Venugopalan, S., Rohrbach, M., Donahue, J., Mooney, R., Darrell, T., Saenko, K.: Sequence to sequence - video to text. In: Proceedings of IEEE International Conference on Computer Vision, pp. 4534\u20134542 (2015)","DOI":"10.1109\/ICCV.2015.515"},{"key":"41_CR38","doi-asserted-by":"crossref","unstructured":"Venugopalan, S., Xu, H., Donahue, J., Rohrbach, M., Mooney, R., Saenko, K.: Translating videos to natural language using deep recurrent neural networks. In: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1494\u20131504 (2015)","DOI":"10.3115\/v1\/N15-1173"},{"key":"41_CR39","doi-asserted-by":"crossref","unstructured":"Wang, B., Ma, L., Zhang, W., Liu, W.: Reconstruction network for video captioning. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 7622\u20137631 (2018)","DOI":"10.1109\/CVPR.2018.00795"},{"key":"41_CR40","doi-asserted-by":"crossref","unstructured":"Yang, H.D., Lee, S.W.: Robust sign language recognition with hierarchical conditional random fields. In: Proceedings of IEEE International Conference on Pattern Recognition, pp. 2202\u20132205 (2010)","DOI":"10.1109\/ICPR.2010.539"},{"key":"41_CR41","doi-asserted-by":"crossref","unstructured":"Yang, R., Sarkar, S.: Detecting coarticulation in sign language using conditional random fields. In: Proceedings of IEEE International Conference on Pattern Recognition, pp. 108\u2013112 (2006)","DOI":"10.1109\/ICPR.2006.431"},{"key":"41_CR42","unstructured":"Yang, R., Sarkar, S.: Gesture recognition using hidden Markov models from fragmented observations. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 766\u2013773 (2006)"},{"key":"41_CR43","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.patrec.2016.03.030","volume":"78","author":"W Yang","year":"2016","unstructured":"Yang, W., Tao, J., Ye, Z.: Continuous sign language recognition using level building based on fast hidden Markov model. Pattern Recogn. Lett. 78, 28\u201335 (2016)","journal-title":"Pattern Recogn. Lett."},{"key":"41_CR44","unstructured":"Yang, Z., Shi, Z., Shen, X., Tai, Y.W.: SF-net: structured feature network for continuous sign language recognition. arXiv preprint arXiv:1908.01341 (2019)"},{"key":"41_CR45","doi-asserted-by":"crossref","unstructured":"Yao, L., et al.: Describing videos by exploiting temporal structure. In: Proceedings of IEEE International Conference on Computer Vision, pp. 4507\u20134515 (2015)","DOI":"10.1109\/ICCV.2015.512"},{"key":"41_CR46","doi-asserted-by":"crossref","unstructured":"Yin, F., Chai, X., Zhou, Y., Chen, X.: Weakly supervised metric learning towards signer adaptation for sign language recognition. In: Proceedings of British Machine Vision Conference, pp. 35.1\u201335.12 (2015)","DOI":"10.5244\/C.29.35"},{"key":"41_CR47","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhou, W., Li, H.: A threshold-based HMM-DTW approach for continuous sign language recognition. In: Proceedings of International Conference on Internet Multimedia Computing and Service, pp. 237\u2013240 (2014)","DOI":"10.1145\/2632856.2632931"},{"key":"41_CR48","doi-asserted-by":"crossref","unstructured":"Zhang, J., Zhou, W., Xie, C., Pu, J., Li, H.: Chinese sign language recognition with adaptive HMM. In: Proceedings of IEEE International Conference on Multimedia and Expo, pp. 1\u20136 (2016)","DOI":"10.1109\/ICME.2016.7552950"},{"key":"41_CR49","doi-asserted-by":"crossref","unstructured":"Zhou, H., Zhou, W., Zhou, Y., Li, H.: Spatial-temporal multi-cue network for continuous sign language recognition. In: Proceedings of AAAI Conference on Artificial Intelligence, pp. 13009\u201313016 (2020)","DOI":"10.1609\/aaai.v34i07.7001"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58586-0_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T00:18:29Z","timestamp":1732839509000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58586-0_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585853","9783030585860"],"references-count":49,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58586-0_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"30 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","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":"23 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2020.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"OpenReview","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5025","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":"1360","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":"0","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":"27% - 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":"3","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":"7","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":"The conference was held virtually due to the COVID-19 pandemic. From the ECCV Workshops 249 full papers, 18 short papers, and 21 further contributions were published out of a total of 467 submissions.","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)"}}]}}