{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T11:47:52Z","timestamp":1743767272588,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"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_15","type":"book-chapter","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:03:53Z","timestamp":1666825433000},"page":"179-188","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["GPU-Accelerated Infrared Patch-Image Model for Small Target Detection"],"prefix":"10.1007","author":[{"given":"Xuying","family":"Hao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujia","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunjing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,27]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Schwering, P.B., Bezuidenhout, D.F., Gunter, W. H., le Roux, F.P., Sieberhagen, R.H.: IRST infrared background analysis of bay environments. In: Infrared Technology and Applications XXXIV, vol. 6940, pp. 467\u2013478. SPIE (2008)","key":"15_CR1","DOI":"10.1117\/12.778449"},{"key":"15_CR2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2020.3040221","volume":"60","author":"C Zhang","year":"2021","unstructured":"Zhang, C., He, Y., Tang, Q., Chen, Z., Mu, T.: Infrared small target detection via interpatch correlation enhancement and joint local visual saliency prior. IEEE Trans. Geosci. Remote Sens. 60, 1\u201314 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"15_CR3","first-page":"1","volume":"60","author":"G Wang","year":"2021","unstructured":"Wang, G., Tao, B., Kong, X., Peng, Z.: Infrared small target detection using nonoverlapping patch spatial-temporal tensor factorization with capped nuclear norm regularization. IEEE Trans. Geosci. Remote Sens. 60, 1\u201317 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"doi-asserted-by":"crossref","unstructured":"Deshpande, S.D., Er, M.H., Venkateswarlu, R., Chan, P.: Max-mean and max-median filters for detection of small targets. In: Signal and Data Processing of Small Targets 1999, vol. 3809, pp. 74\u201383. SPIE (1999)","key":"15_CR4","DOI":"10.1117\/12.364049"},{"issue":"3","key":"15_CR5","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1049\/el:20092206","volume":"45","author":"P Wang","year":"2009","unstructured":"Wang, P., Tian, J., Gao, C.Q.: Infrared small target detection using directional highpass filters based on LS-SVM. Electron. Lett. 45(3), 156\u2013158 (2009)","journal-title":"Electron. Lett."},{"issue":"4","key":"15_CR6","first-page":"408","volume":"9","author":"H Zhang","year":"2004","unstructured":"Zhang, H., Lei, Z.H., Ding, X.H.: An improved method of median filter. J. Image Graph. 9(4), 408\u2013411 (2004)","journal-title":"J. Image Graph."},{"issue":"6","key":"15_CR7","doi-asserted-by":"crossref","first-page":"2145","DOI":"10.1016\/j.patcog.2009.12.023","volume":"43","author":"X Bai","year":"2010","unstructured":"Bai, X., Zhou, F.: Analysis of new top-hat transformation and the application for infrared dim small target detection. Pattern Recogn. 43(6), 2145\u20132156 (2010)","journal-title":"Pattern Recogn."},{"issue":"2","key":"15_CR8","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"J Wright","year":"2008","unstructured":"Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(2), 210\u2013227 (2008)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"15_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jvcir.2018.10.008","volume":"57","author":"M Jian","year":"2018","unstructured":"Jian, M., et al.: Saliency detection based on directional patches extraction and principal local color contrast. J. Vis. Commun. Image Represent. 57, 1\u201311 (2018)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"12","key":"15_CR10","doi-asserted-by":"crossref","first-page":"4996","DOI":"10.1109\/TIP.2013.2281420","volume":"22","author":"C Gao","year":"2013","unstructured":"Gao, C., Meng, D., Yang, Y., Wang, Y., Zhou, X., Hauptmann, A.G.: Infrared patch-image model for small target detection in a single image. IEEE Trans. Image Process. 22(12), 4996\u20135009 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"15_CR11","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1016\/j.infrared.2016.06.021","volume":"77","author":"Y Dai","year":"2016","unstructured":"Dai, Y., Wu, Y., Song, Y.: Infrared small target and background separation via column-wise weighted robust principal component analysis. Infrared Phys. Technol. 77, 421\u2013430 (2016)","journal-title":"Infrared Phys. Technol."},{"key":"15_CR12","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.infrared.2017.01.009","volume":"81","author":"Y Dai","year":"2017","unstructured":"Dai, Y., Wu, Y., Song, Y., Guo, J.: Non-negative infrared patch-image model: robust target-background separation via partial sum minimization of singular values. Infrared Phys. Technol. 81, 182\u2013194 (2017)","journal-title":"Infrared Phys. Technol."},{"issue":"11","key":"15_CR13","doi-asserted-by":"crossref","first-page":"1821","DOI":"10.3390\/rs10111821","volume":"10","author":"L Zhang","year":"2018","unstructured":"Zhang, L., Peng, L., Zhang, T., Cao, S., Peng, Z.: Infrared small target detection via non-convex rank approximation minimization joint l 2, 1 norm. Remote Sens. 10(11), 1821 (2018)","journal-title":"Remote Sens."},{"issue":"5","key":"15_CR14","doi-asserted-by":"crossref","first-page":"559","DOI":"10.3390\/rs11050559","volume":"11","author":"T Zhang","year":"2019","unstructured":"Zhang, T., Wu, H., Liu, Y., Peng, L., Yang, C., Peng, Z.: Infrared small target detection based on non-convex optimization with LP-norm constraint. Remote Sens. 11(5), 559 (2019)","journal-title":"Remote Sens."},{"issue":"8","key":"15_CR15","doi-asserted-by":"crossref","first-page":"3752","DOI":"10.1109\/JSTARS.2017.2700023","volume":"10","author":"Y Dai","year":"2017","unstructured":"Dai, Y., Wu, Y.: Reweighted infrared patch-tensor model with both nonlocal and local priors for single-frame small target detection. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 10(8), 3752\u20133767 (2017)","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"issue":"4","key":"15_CR16","doi-asserted-by":"crossref","first-page":"382","DOI":"10.3390\/rs11040382","volume":"11","author":"L Zhang","year":"2019","unstructured":"Zhang, L., Peng, Z.: Infrared small target detection based on partial sum of the tensor nuclear norm. Remote Sens. 11(4), 382 (2019)","journal-title":"Remote Sens."},{"key":"15_CR17","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.neucom.2020.08.065","volume":"420","author":"T Zhang","year":"2021","unstructured":"Zhang, T., Peng, Z., Wu, H., He, Y., Li, C., Yang, C.: Infrared small target detection via self-regularized weighted sparse model. Neurocomputing 420, 124\u2013148 (2021)","journal-title":"Neurocomputing"}],"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_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:42:06Z","timestamp":1666827726000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18916-6_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031189159","9783031189166"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18916-6_15","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)"}}]}}