{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T14:32:36Z","timestamp":1784644356872,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":19,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811623356","type":"print"},{"value":"9789811623363","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-2336-3_50","type":"book-chapter","created":{"date-parts":[[2021,5,4]],"date-time":"2021-05-04T16:17:17Z","timestamp":1620145037000},"page":"527-537","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Semantic-Based Road Segmentation for High-Definition Map Construction"],"prefix":"10.1007","author":[{"given":"Hanyang","family":"Zhuang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunxiang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhan","family":"Qian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,5,5]]},"reference":[{"key":"50_CR1","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.imavis.2017.07.003","volume":"68","author":"C H\u00e4ne","year":"2017","unstructured":"H\u00e4ne, C., et al.: 3D visual perception for self-driving cars using a multi-camera system: Calibration, mapping, localization, and obstacle detection. Image Vis. Comput. 68, 14\u201327 (2017)","journal-title":"Image Vis. Comput."},{"issue":"1","key":"50_CR2","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/s12239-018-0018-z","volume":"19","author":"U Lee","year":"2018","unstructured":"Lee, U., et al.: Development of a self-driving car that can handle the adverse weather. Int. J. Autom. Technol. 19(1), 191\u2013197 (2018)","journal-title":"Int. J. Autom. Technol."},{"key":"50_CR3","first-page":"274","volume":"S1","author":"Y He","year":"2015","unstructured":"He, Y., et al.: Generation of precise lane-level maps based on multi-sensors. J. Chang\u2019an Univ. (Nat. Sci. Edn.) S1, 274\u2013278 (2015)","journal-title":"J. Chang\u2019an Univ. (Nat. Sci. Edn.)"},{"key":"50_CR4","doi-asserted-by":"crossref","unstructured":"Li, L., et al.: An overview on sensor map based localization for automated driving. In: 2017 Joint Urban Remote Sensing Event (JURSE), pp. 1\u20134 (2017)","DOI":"10.1109\/JURSE.2017.7924575"},{"key":"50_CR5","doi-asserted-by":"crossref","unstructured":"Lindong, G., et al.: Occupancy grid based urban localization using weighted point cloud. In: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp. 60\u201365 (2016)","DOI":"10.1109\/ITSC.2016.7795532"},{"issue":"1","key":"50_CR6","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62\u201366 (1979)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"50_CR7","doi-asserted-by":"crossref","unstructured":"Lakshmi, S., Sankaranarayanan, D.V.: A study of edge detection techniques for segmentation computing approaches. In: IJCA Special Issue on \u201cComputer Aided Soft Computing Techniques for Imaging and Biomedical Applications\u201d, pp. 35\u201340 (2010)","DOI":"10.5120\/993-25"},{"issue":"4","key":"50_CR8","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"L Chen","year":"2018","unstructured":"Chen, L., et al.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834\u2013848 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"50_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1007\/978-3-030-01234-2_49","volume-title":"Computer Vision \u2013 ECCV 2018","author":"L-C Chen","year":"2018","unstructured":"Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 833\u2013851. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_49"},{"issue":"4","key":"50_CR10","doi-asserted-by":"publisher","first-page":"640","DOI":"10.1109\/TPAMI.2016.2572683","volume":"39","author":"E Shelhamer","year":"2017","unstructured":"Shelhamer, E., Long, J., Darrell, T.: Fully convolutional networks for semantic segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(4), 640\u2013651 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"50_CR11","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems 27 (NIPS 2014), pp. 2672\u20132680 (2014)"},{"key":"50_CR12","doi-asserted-by":"crossref","unstructured":"Nguyen, V., et al.: Shadow detection with conditional generative adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 4510\u20134518 (2017)","DOI":"10.1109\/ICCV.2017.483"},{"key":"50_CR13","doi-asserted-by":"crossref","unstructured":"Fredembach, C., Finlayson, G.: Simple shadow removal. In: 18th International Conference on Pattern Recognition (ICPR 2006), pp. 832\u2013835 (2006)","DOI":"10.1109\/ICPR.2006.1054"},{"key":"50_CR14","doi-asserted-by":"crossref","unstructured":"Wang, J., Li, X., Yang, J.: Stacked conditional generative adversarial networks for jointly learning shadow detection and shadow removal. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1788\u20131797 (2018)","DOI":"10.1109\/CVPR.2018.00192"},{"issue":"8","key":"50_CR15","first-page":"158","volume":"36","author":"K Shen","year":"2017","unstructured":"Shen, K., Guang, X., Li, W.: Application of EKF in integrated navigation system. Trans. Microsyst. Technol. 36(8), 158\u2013160 (2017)","journal-title":"Trans. Microsyst. Technol."},{"issue":"1","key":"50_CR16","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1364\/JOT.82.000028","volume":"82","author":"Y Fan","year":"2015","unstructured":"Fan, Y., et al.: Study on a stitching algorithm of the iterative closest point based on dynamic hierarchy. J. Opt. Technol. 82(1), 28\u201332 (2015)","journal-title":"J. Opt. Technol."},{"issue":"2","key":"50_CR17","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91\u2013110 (2004)","journal-title":"Int. J. Comput. Vis."},{"issue":"6","key":"50_CR18","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981)","journal-title":"Commun. ACM"},{"issue":"2","key":"50_CR19","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"PJ Besl","year":"1992","unstructured":"Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239\u2013256 (1992)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Communications in Computer and Information Science","Cognitive Systems and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-2336-3_50","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,4]],"date-time":"2021-05-04T16:54:58Z","timestamp":1620147298000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-2336-3_50"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811623356","9789811623363"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-2336-3_50","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"5 May 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Cognitive Systems and Signal Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhuhai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"25 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsip2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iccsip2020.caai.cn\/","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":"120","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":"59","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":"49% - 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","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":"3","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}