{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T12:56:23Z","timestamp":1726059383967},"publisher-location":"Cham","reference-count":8,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030352301"},{"type":"electronic","value":"9783030352318"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-35231-8_49","type":"book-chapter","created":{"date-parts":[[2019,11,16]],"date-time":"2019-11-16T00:30:38Z","timestamp":1573864238000},"page":"671-680","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Efficient Gaussian Distance Transforms for Image Processing"],"prefix":"10.1007","author":[{"given":"Senjian","family":"An","sequence":"first","affiliation":[]},{"given":"Yiwei","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Wanquan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ling","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,11,15]]},"reference":[{"issue":"2","key":"49_CR1","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/BF01840359","volume":"60","author":"A Aggarwal","year":"1987","unstructured":"Aggarwal, A., Klawe, M.M., Moran, S., Shor, P., Wilber, R.: Geometric applications of a matrix-searching algorithm. Algorithmica 60(2), 195\u2013208 (1987)","journal-title":"Algorithmica"},{"issue":"1","key":"49_CR2","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1145\/1322432.1322434","volume":"40","author":"R Fabbri","year":"2008","unstructured":"Fabbri, R., Costa, L.D.F., Torelli, J.C., Bruno, O.M.: 2D euclidean distance transform algorithms: a comparative survey. ACM Comput. Surv. (CSUR) 40(1), 2 (2008)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"9","key":"49_CR3","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"P Felzenszwalb","year":"2010","unstructured":"Felzenszwalb, P., Girshick, R., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627\u20131645 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"49_CR4","unstructured":"Felzenszwalb, P., Huttenlocher, D.: Distance transforms of sampled functions. Technical Report TR2004-1963, Conell Computing and Information Science (2004)"},{"key":"49_CR5","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1007\/0-306-47025-X_36","volume-title":"Mathematical Morphology and Its Applications to Image and Signal Processing","author":"A Meijster","year":"2002","unstructured":"Meijster, A., Roerdink, J.B., Hesselink, W.H.: A general algorithm for computing distance transforms in linear time. In: Goutsias, J., Vincent, L., Bloomberg, D.S. (eds.) Mathematical Morphology and Its Applications to Image and Signal Processing, pp. 331\u2013340. Springer, Boston (2002)"},{"key":"49_CR6","doi-asserted-by":"crossref","unstructured":"Pandey, M., Lazebnik, S.: Scene recognition and weakly supervised object localization with deformable part-based models. In: 2011 International Conference on Computer Vision, pp. 1307\u20131314. IEEE (2011)","DOI":"10.1109\/ICCV.2011.6126383"},{"key":"49_CR7","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.ins.2018.08.038","volume":"470","author":"LC Ribas","year":"2019","unstructured":"Ribas, L.C., Neiva, M.B., Bruno, O.M.: Distance transform network for shape analysis. Inf. Sci. 470, 28\u201342 (2019)","journal-title":"Inf. Sci."},{"issue":"5","key":"49_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1618452.1618493","volume":"28","author":"Kartic Subr","year":"2009","unstructured":"Subr, K., Soler, C., Durand, F.: Edge-preserving multiscale image decomposition based on local extrema. In: ACM Transactions on Graphics (TOG), vol. 28, p. 147. ACM (2009)","journal-title":"ACM Transactions on Graphics"}],"container-title":["Lecture Notes in Computer Science","Advanced Data Mining and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-35231-8_49","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,16]],"date-time":"2019-11-16T00:43:08Z","timestamp":1573864988000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-35231-8_49"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030352301","9783030352318"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-35231-8_49","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"15 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ADMA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Data Mining and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dalian","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"adma2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/adma2019.neusoft.edu.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":"170","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":"39","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":"26","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":"23% - 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":"7","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)"}}]}}