{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T04:45:49Z","timestamp":1765169149552,"version":"3.46.0"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032049674"},{"type":"electronic","value":"9783032049681"}],"license":[{"start":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T00:00:00Z","timestamp":1758067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T00:00:00Z","timestamp":1758067200000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-04968-1_13","type":"book-chapter","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T08:04:59Z","timestamp":1758009899000},"page":"151-162","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Walk the\u00a0Lines 2: Contour Tracking for\u00a0Detailed Segmentation of\u00a0Infrared Ships and\u00a0Other Objects"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4146-7953","authenticated-orcid":false,"given":"Andr\u00e9 Peter","family":"Kelm","sequence":"first","affiliation":[]},{"given":"Max","family":"Braeschke","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3834-3645","authenticated-orcid":false,"given":"Emre","family":"G\u00fclsoylu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9475-3593","authenticated-orcid":false,"given":"Simone","family":"Frintrop","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,17]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","first-page":"117908","DOI":"10.1109\/ACCESS.2024.3448301","volume":"12","author":"I Ali Ibrahim","year":"2024","unstructured":"Ali Ibrahim, I., Namoun, A., Ullah, S., Alasmary, H., Waqas, M., Ahmad, I.: Infrared ship segmentation based on weakly-supervised and semi-supervised learning. IEEE Access 12, 117908\u2013117920 (2024)","journal-title":"IEEE Access"},{"issue":"5","key":"13_CR2","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","volume":"33","author":"P Arbel\u00e1ez","year":"2011","unstructured":"Arbel\u00e1ez, P., Maire, M., Fowlkes, C., Malik, J.: Contour detection and hierarchical image segmentation. TPAMI 33(5), 898\u2013916 (2011)","journal-title":"TPAMI"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Bhattacharya, P., Riechen, J., Z\u00f6lzer, U.: Infrared image enhancement in maritime environment with CNNs. In: VISAPP, pp. 37\u201346. SciTePress (2018)","DOI":"10.5220\/0006618700370046"},{"key":"13_CR4","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","volume":"6","author":"J Canny","year":"1986","unstructured":"Canny, J.: A computational approach to edge detection. TPAMI 6, 679\u2013698 (1986)","journal-title":"TPAMI"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Chen, C., Hu, S., Ma, F., Sun, J., Lu, T., Wu, B.: Ship contour: a novel ship instance segmentation method using deep snake and attention mechanism. J. Mar. Sci. Eng. 13(3) (2025)","DOI":"10.3390\/jmse13030519"},{"key":"13_CR6","unstructured":"Chen, J., Bai, X.: Learning to \u201csegment anything\u201d in thermal infrared images through knowledge distillation with a large scale dataset satir (2023). https:\/\/arxiv.org\/abs\/2304.07969"},{"key":"13_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2024.119368","volume":"313","author":"X Chen","year":"2024","unstructured":"Chen, X., Chen, W., Wu, B., Wu, H., Xian, J.: Ship visual trajectory exploitation via an ensemble instance segmentation framework. Ocean Eng. 313, 119368 (2024)","journal-title":"Ocean Eng."},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Chen, X., Qiu, C., Zhang, Z.: A multiscale method for infrared ship detection based on morphological reconstruction and two-branch compensation strategy. Sensors 23(16) (2023)","DOI":"10.3390\/s23167309"},{"key":"13_CR9","unstructured":"Ke, L., et al.: Segment anything in high quality. In: NeurIPS (2023)"},{"key":"13_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1007\/978-3-030-29888-3_20","volume-title":"Computer Analysis of Images and Patterns","author":"AP Kelm","year":"2019","unstructured":"Kelm, A.P., Rao, V.S., Z\u00f6lzer, U.: Object contour and edge detection with RefineContourNet. In: Vento, M., Percannella, G. (eds.) CAIP 2019. LNCS, vol. 11678, pp. 246\u2013258. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-29888-3_20"},{"key":"13_CR11","unstructured":"Kelm, A.P.: Extraktion geschlossener Schiffs- und Objektkonturen mit 1-Pixel-Breite zur pr\u00e4zisen Segmentierung in Farb- und Infrarotbildern durch Deep Learning. Ph.D. thesis, Helmut Schmidt University, Holstenhofweg 85, 22043 Hamburg, Germany (2025), doctoral dissertation, expected 2025"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Kelm, A.P., Z\u00f6lzer, U.: Walk the lines: object contour tracing CNN for contour completion of ships. In: ICPR, pp. 3993\u20134000 (2021)","DOI":"10.1109\/ICPR48806.2021.9412410"},{"key":"13_CR13","unstructured":"Kim, Y., Park, J., Kang, S., Kim, H.: Introducing VaDA: novel image segmentation model for maritime object segmentation using new dataset (2024). https:\/\/arxiv.org\/abs\/2407.09005"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Kirillov, A., et al.: Segment anything. In: ICCV, pp. 3992\u20134003 (2023)","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"13_CR15","unstructured":"Kr\u00e4henb\u00fchl, P., Koltun, V.: Efficient inference in fully connected CRFs with gaussian edge potentials. In: Neurips, vol.\u00a024 (2011)"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Lin, G., Liu, F., Milan, A., Shen, C., Reid, I.: RefineNet: multi-path refinement networks for dense prediction. TPAMI (2019)","DOI":"10.1109\/TPAMI.2019.2893630"},{"key":"13_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Ling, H., Gao, J., Kar, A., Chen, W., Fidler, S.: Fast interactive object annotation with curve-GCN. In: CVPR, pp. 5252\u20135261 (2019)","DOI":"10.1109\/CVPR.2019.00540"},{"key":"13_CR19","unstructured":"Mantell, S.: Free deer image. Online: Pixabay. https:\/\/pixabay.com\/de\/photos\/rentier-hirsch-brown-tier-geweih-1323000. Accessed 20 Mar 2023"},{"issue":"7","key":"13_CR20","first-page":"3523","volume":"44","author":"S Minaee","year":"2022","unstructured":"Minaee, S., Boykov, Y., Porikli, F., Plaza, A., Kehtarnavaz, N., Terzopoulos, D.: Image segmentation using deep learning: a survey. TPAMI 44(7), 3523\u20133542 (2022)","journal-title":"TPAMI"},{"issue":"1\u20132","key":"13_CR21","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1177\/02783649231153020","volume":"42","author":"S Nirgudkar","year":"2023","unstructured":"Nirgudkar, S., DeFilippo, M., Sacarny, M., Benjamin, M., Robinette, P.: Massmind: Massachusetts maritime infrared dataset. Int. J. Robot. Res. 42(1\u20132), 21\u201332 (2023)","journal-title":"Int. J. Robot. Res."},{"key":"13_CR22","doi-asserted-by":"crossref","unstructured":"Peng, S., Jiang, W., Pi, H., Li, X., Bao, H., Zhou, X.: Deep snake for real-time instance segmentation. In: CVPR (2020)","DOI":"10.1109\/CVPR42600.2020.00856"},{"key":"13_CR23","doi-asserted-by":"crossref","unstructured":"Xie, E., et al.: Polarmask: single shot instance segmentation with polar representation. In: CVPR, pp. 12190\u201312199 (2020)","DOI":"10.1109\/CVPR42600.2020.01221"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, M., Wang, Y., Guo, J., Li, Y., Gao, X., Zhang, J.: Irsam: advancing segment anything model for infrared small target detection. In: ECCV, pp. 233\u2013249 (2024)","DOI":"10.1007\/978-3-031-72855-6_14"},{"issue":"11","key":"13_CR25","doi-asserted-by":"publisher","first-page":"17778","DOI":"10.1109\/TITS.2024.3404973","volume":"25","author":"M Zhang","year":"2024","unstructured":"Zhang, M., Zhang, Q., Song, R., Rosin, P.L., Zhang, W.: Ship landmark: an informative ship image annotation and its applications. Trans. Intell. Transp. Syst. 25(11), 17778\u201317793 (2024)","journal-title":"Trans. Intell. Transp. Syst."},{"key":"13_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.patrec.2022.09.003","volume":"163","author":"QL Zhang","year":"2022","unstructured":"Zhang, Q.L., Yang, Y.B.: A boundary-preserving conditional convolution network for instance segmentation. Pattern Recogn. Lett. 163, 1\u20139 (2022)","journal-title":"Pattern Recogn. Lett."},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, T., Wei, S., Ji, S.: E2EC: an end-to-end contour-based method for high-quality high-speed instance segmentation. In: CVPR, pp. 4443\u20134452 (2022)","DOI":"10.1109\/CVPR52688.2022.00440"},{"key":"13_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110344","volume":"265","author":"T Zhang","year":"2023","unstructured":"Zhang, T., et al.: Infrared ship target segmentation based on adversarial domain adaptation. Knowl.-Based Syst. 265, 110344 (2023)","journal-title":"Knowl.-Based Syst."}],"container-title":["Lecture Notes in Computer Science","Computer Analysis of Images and Patterns"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-04968-1_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T04:42:30Z","timestamp":1765168950000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-04968-1_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,17]]},"ISBN":["9783032049674","9783032049681"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-04968-1_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,9,17]]},"assertion":[{"value":"17 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CAIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Analysis of Images and Patterns","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Las Palmas de Gran Canaria","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"caip2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/caip2025.com","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}