{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T12:20:55Z","timestamp":1742991655260,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031189159"},{"type":"electronic","value":"9783031189166"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-18916-6_25","type":"book-chapter","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:03:53Z","timestamp":1666825433000},"page":"301-314","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TAFDet: A Task Awareness Focal Detector for Ship Detection in SAR Images"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9611-4464","authenticated-orcid":false,"given":"Yilong","family":"Lv","sequence":"first","affiliation":[]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2299-4945","authenticated-orcid":false,"given":"Yujie","family":"He","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Song","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,27]]},"reference":[{"issue":"1","key":"25_CR1","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1109\/TGRS.2019.2937175","volume":"58","author":"L Du","year":"2020","unstructured":"Du, L., Dai, H., Wang, Y., Xie, W., Wang, Z.: Target discrimination based on weakly supervised learning for high-resolution SAR images in complex scenes. IEEE Trans. Geosci. Remote Sens. 58(1), 461\u2013472 (2020)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"25_CR2","doi-asserted-by":"publisher","first-page":"1100","DOI":"10.1109\/TGRS.2018.2864716","volume":"57","author":"M Shahzad","year":"2019","unstructured":"Shahzad, M., Maurer, M., Fraundorfer, F., Wang, Y., Zhu, X.X.: Buildings detection in VHR SAR images using fully convolution neural networks. IEEE Trans. Geosci. Remote Sens. 57(2), 1100\u20131116 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"25_CR3","doi-asserted-by":"crossref","unstructured":"Huang, L., et al.: OpenSARShip: a dataset dedicated to Sentinel-1 ship interpretation. IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. 11(1), 195\u2013208 (2018)","DOI":"10.1109\/JSTARS.2017.2755672"},{"issue":"12","key":"25_CR4","doi-asserted-by":"publisher","first-page":"7177","DOI":"10.1109\/TGRS.2017.2743222","volume":"55","author":"Z Zhang","year":"2017","unstructured":"Zhang, Z., Wang, H., Xu, F., Jin, Y.-Q.: Complex-valued convolutional neural network and its application in polarimetric SAR image classification. IEEE Trans. Geosci. Remote Sens. 55(12), 7177\u20137188 (2017)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"5","key":"25_CR5","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1109\/LGRS.2018.2879969","volume":"16","author":"G Yang","year":"2019","unstructured":"Yang, G., Li, H.-C., Yang, W., Fu, K., Sun, Y.-J., Emery, W.J.: Unsupervised change detection of SAR images based on variational multivariate Gaussian mixture model and Shannon entropy. IEEE Geosci. Remote Sens. Lett. 16(5), 826\u2013830 (2019)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"4","key":"25_CR6","doi-asserted-by":"publisher","first-page":"2031","DOI":"10.1109\/TGRS.2018.2870716","volume":"57","author":"CH Gierull","year":"2019","unstructured":"Gierull, C.H.: Demystifying the capability of sublook correlation techniques for vessel detection in SAR imagery. IEEE Trans. Geosci. Remote Sens. 57(4), 2031\u20132042 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"6","key":"25_CR7","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: towards real-time target detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"25_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/978-3-319-46448-0_2","volume-title":"Computer Vision \u2013 ECCV 2016","author":"W Liu","year":"2016","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., Berg, A.C.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21\u201337. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2"},{"issue":"2","key":"25_CR10","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","volume":"42","author":"T Lin","year":"2020","unstructured":"Lin, T., Goyal, P., Girshick, R., He, K., Dollar, P.: Focal loss for dense object detection. IEEE Trans. Pattern Anal. Mach. Intell. 42(2), 318\u2013327 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"25_CR11","doi-asserted-by":"crossref","unstructured":"Tian, Z., Shen, C., Chen, H., He, T.: FCOS: fully convolutional one-stage object detection. In: Proceedings of IEEE\/CVF International Conference on Computer Vision (2019)","DOI":"10.1109\/ICCV.2019.00972"},{"key":"25_CR12","doi-asserted-by":"crossref","unstructured":"Kong, T., et al.: FoveaBox: beyond anchor-based object detector (2019)","DOI":"10.1109\/TIP.2020.3002345"},{"key":"25_CR13","doi-asserted-by":"crossref","unstructured":"Jiang, B., et al.: Acquisition of localization confidence for accurate object detection (2018)","DOI":"10.1007\/978-3-030-01264-9_48"},{"key":"25_CR14","doi-asserted-by":"crossref","unstructured":"Wang, N., et al.: NAS-FCOS: fast neural architecture search for object detection. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE (2020)","DOI":"10.1109\/CVPR42600.2020.01196"},{"key":"25_CR15","doi-asserted-by":"crossref","unstructured":"Dai, X., et al.: Dynamic head: Unifying object detection heads with attentions (2021)","DOI":"10.1109\/CVPR46437.2021.00729"},{"key":"25_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-01234-2_1","volume-title":"Computer Vision \u2013 ECCV 2018","author":"S Woo","year":"2018","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: CBAM: convolutional block attention module. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 3\u201319. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_1"},{"key":"25_CR17","doi-asserted-by":"crossref","unstructured":"Huang, Z., Ke, W., Huang, D.: Improving object detection with inverted attention. arXiv:1903.12255 (2019)","DOI":"10.1109\/WACV45572.2020.9093507"},{"key":"25_CR18","doi-asserted-by":"crossref","unstructured":"Feng, C., et al.: TOOD: task-aligned one-stage object detection (2021)","DOI":"10.1109\/ICCV48922.2021.00349"},{"key":"25_CR19","unstructured":"Li, X., et al.: Generalized focal loss: learning qualified and distributed bounding boxes for dense objectdetection. arXiv preprint arXiv:2006.04388 (2020)"},{"key":"25_CR20","doi-asserted-by":"crossref","unstructured":"Cao, Y., Chen, K., Loy, C.C., Lin, D.: Prime sample attention in object detection. arXivpreprint arXiv:1904.04821 (2019)","DOI":"10.1109\/CVPR42600.2020.01160"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18916-6_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:43:46Z","timestamp":1666827826000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18916-6_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031189159","9783031189166"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18916-6_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"27 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenzhen","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2022","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":"ccprcv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/en.prcv.cn\/","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":"microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"564","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":"233","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":"41% - 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":"3.03","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":"3.35","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)"}}]}}