{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T09:35:25Z","timestamp":1766050525690,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031510229"},{"type":"electronic","value":"9783031510236"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-51023-6_3","type":"book-chapter","created":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T07:02:36Z","timestamp":1705993356000},"page":"28-38","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["MARS: Mask Attention Refinement with\u00a0Sequential Quadtree Nodes for\u00a0Car Damage Instance Segmentation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8464-4476","authenticated-orcid":false,"given":"Teerapong","family":"Panboonyuen","sequence":"first","affiliation":[]},{"given":"Naphat","family":"Nithisopa","sequence":"additional","affiliation":[]},{"given":"Panin","family":"Pienroj","sequence":"additional","affiliation":[]},{"given":"Laphonchai","family":"Jirachuphun","sequence":"additional","affiliation":[]},{"given":"Chaiwasut","family":"Watthanasirikrit","sequence":"additional","affiliation":[]},{"given":"Naruepon","family":"Pornwiriyakul","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,24]]},"reference":[{"issue":"1","key":"3_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-021-00539-2","volume":"8","author":"M Amirfakhrian","year":"2021","unstructured":"Amirfakhrian, M., Parhizkar, M.: Integration of image segmentation and fuzzy theory to improve the accuracy of damage detection areas in traffic accidents. J. Big Data 8(1), 1\u201317 (2021)","journal-title":"J. Big Data"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Arnab, A., Torr, P.H.: Pixelwise instance segmentation with a dynamically instantiated network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 441\u2013450 (2017)","DOI":"10.1109\/CVPR.2017.100"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Bolya, D., Zhou, C., Xiao, F., Lee, Y.J.: YOLACT: real-time instance segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9157\u20139166 (2019)","DOI":"10.1109\/ICCV.2019.00925"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Chen, H., Sun, K., Tian, Z., Shen, C., Huang, Y., Yan, Y.: BlendMask: top-down meets bottom-up for instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8573\u20138581 (2020)","DOI":"10.1109\/CVPR42600.2020.00860"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Chen, K., et al.: Hybrid task cascade for instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4974\u20134983 (2019)","DOI":"10.1109\/CVPR.2019.00511"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Hermans, A., Papandreou, G., Schroff, F., Wang, P., Adam, H.: MaskLab: instance segmentation by refining object detection with semantic and direction features. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4013\u20134022 (2018)","DOI":"10.1109\/CVPR.2018.00422"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Deng, D., Liu, H., Li, X., Cai, D.: PixelLink: detecting scene text via instance segmentation. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.12269"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Iglovikov, V., Seferbekov, S., Buslaev, A., Shvets, A.: TernausNetV2: fully convolutional network for instance segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 233\u2013237 (2018)","DOI":"10.1109\/CVPRW.2018.00042"},{"key":"3_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.socec.2023.101993","volume":"103","author":"K J\u00f5eveer","year":"2023","unstructured":"J\u00f5eveer, K., Kepp, K.: What drives drivers? Switching, learning, and the impact of claims in car insurance. J. Behav. Exp. Econ. 103, 101993 (2023)","journal-title":"J. Behav. Exp. Econ."},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Ke, L., Danelljan, M., Li, X., Tai, Y.W., Tang, C.K., Yu, F.: Mask transfiner for high-quality instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4412\u20134421 (2022)","DOI":"10.1109\/CVPR52688.2022.00437"},{"key":"3_CR13","doi-asserted-by":"crossref","unstructured":"Kirillov, A., Wu, Y., He, K., Girshick, R.: PointRend: image segmentation as rendering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9799\u20139808 (2020)","DOI":"10.1109\/CVPR42600.2020.00982"},{"key":"3_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijlcj.2021.100456","volume":"65","author":"AM Macedo","year":"2021","unstructured":"Macedo, A.M., Cardoso, C.V., Neto, J.S.M., et al.: Car insurance fraud: the role of vehicle repair workshops. Int. J. Law Crime Justice 65, 100456 (2021)","journal-title":"Int. J. Law Crime Justice"},{"issue":"2","key":"3_CR15","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/s41315-022-00231-5","volume":"6","author":"M Parhizkar","year":"2022","unstructured":"Parhizkar, M., Amirfakhrian, M.: Car detection and damage segmentation in the real scene using a deep learning approach. Int. J. Intell. Robot. Appl. 6(2), 231\u2013245 (2022)","journal-title":"Int. J. Intell. Robot. Appl."},{"issue":"5","key":"3_CR16","doi-asserted-by":"publisher","first-page":"3613","DOI":"10.1007\/s40747-021-00397-8","volume":"8","author":"K Pasupa","year":"2022","unstructured":"Pasupa, K., Kittiworapanya, P., Hongngern, N., Woraratpanya, K.: Evaluation of deep learning algorithms for semantic segmentation of car parts. Complex Intell. Syst. 8(5), 3613\u20133625 (2022)","journal-title":"Complex Intell. Syst."},{"key":"3_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1007\/978-3-030-58452-8_17","volume-title":"Computer Vision \u2013 ECCV 2020","author":"Z Tian","year":"2020","unstructured":"Tian, Z., Shen, C., Chen, H.: Conditional convolutions for instance segmentation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12346, pp. 282\u2013298. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58452-8_17"},{"key":"3_CR18","unstructured":"Wang, X., Zhang, R., Kong, T., Li, L., Shen, C.: SOLOv2: dynamic and fast instance segmentation. Adv. Neural. Inf. Process. Syst. 33, 17721\u201317732 (2020)"},{"issue":"2","key":"3_CR19","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1162\/REST_a_00448","volume":"97","author":"S Weisburd","year":"2015","unstructured":"Weisburd, S.: Identifying moral hazard in car insurance contracts. Rev. Econ. Stat. 97(2), 301\u2013313 (2015)","journal-title":"Rev. Econ. Stat."},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Xie, E., et al.: PolarMask: single shot instance segmentation with polar representation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12193\u201312202 (2020)","DOI":"10.1109\/CVPR42600.2020.01221"},{"key":"3_CR21","doi-asserted-by":"publisher","first-page":"6997","DOI":"10.1109\/ACCESS.2020.2964055","volume":"8","author":"Q Zhang","year":"2020","unstructured":"Zhang, Q., Chang, X., Bian, S.B.: Vehicle-damage-detection segmentation algorithm based on improved mask RCNN. IEEE Access 8, 6997\u20137004 (2020)","journal-title":"IEEE Access"}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Processing - ICIAP 2023 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-51023-6_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T07:03:11Z","timestamp":1705993391000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-51023-6_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031510229","9783031510236"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-51023-6_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"24 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Udine","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciap2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iciap2023.org\/","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"144","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":"82","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":"13","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":"57% - 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":"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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"https:\/\/iciap2023.org\/satellite-event\/workshops\/","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)"}}]}}