{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:26:48Z","timestamp":1740122808296,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No. 61866002"],"award-info":[{"award-number":["Grant No. 61866002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012547","name":"Natural Science Foundation of Guangxi Zhuang Autonomous Region","doi-asserted-by":"publisher","award":["Grant No.2020GXNSFDA297006","Grant No.2018GXNSFAA138122","Grant No.2015GXNSFAA139293"],"award-info":[{"award-number":["Grant No.2020GXNSFDA297006","Grant No.2018GXNSFAA138122","Grant No.2015GXNSFAA139293"]}],"id":[{"id":"10.13039\/100012547","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s11042-022-13430-w","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T05:02:40Z","timestamp":1658120560000},"page":"3895-3910","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Information recombination network for contour detection"],"prefix":"10.1007","volume":"82","author":[{"given":"Zeqi","family":"Wen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1779-1753","authenticated-orcid":false,"given":"Chuan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuzhang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linhao","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,18]]},"reference":[{"issue":"1","key":"13430_CR1","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/S0146-664X(81)80011-1","volume":"17","author":"JF Abramatic","year":"1981","unstructured":"Abramatic JF (1981) Why the simplest \u201cHueckel\u201d edge detector is a Roberts operator. Computer Graphics & Image Processing 17(1):79\u201383. https:\/\/doi.org\/10.1016\/S0146-664X(81)80011-1","journal-title":"Computer Graphics & Image Processing"},{"issue":"5","key":"13430_CR2","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","volume":"33","author":"P Arbelaez","year":"2011","unstructured":"Arbelaez P, Maire M, Fowlkes C, Malik J (2011) Contour detection and hierarchical image segmentation. IEEE Trans Pattern Anal Mach Intell 33(5):898\u2013916. https:\/\/doi.org\/10.1109\/TPAMI.2010.161","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"publisher","unstructured":"Arbelaez P, Pont-Tuset J, Barron J, Marques F, and Malik J (2014) Multiscale combinatorial grouping. 2014 IEEE conference on computer vision and pattern recognition (CVPR), pp 328-335. https:\/\/doi.org\/10.1109\/CVPR.2014.49","key":"13430_CR3","DOI":"10.1109\/CVPR.2014.49"},{"key":"13430_CR4","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1016\/j.neucom.2019.01.110","volume":"392","author":"M Baldeon-Calisto","year":"2020","unstructured":"Baldeon-Calisto M, Lai-Yuen SK (2020) AdaResU-net: multiobjective adaptive convolutional neural network for medical image segmentation. Neurocomputing. 392:325\u2013340. https:\/\/doi.org\/10.1016\/j.neucom.2019.01.110","journal-title":"Neurocomputing."},{"doi-asserted-by":"publisher","unstructured":"Bertasius G, Shi J, and Torresani L (2015) Deepedge: a multi-scale bifurcated deep network for top-down contour detection. Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4380-4389. https:\/\/doi.org\/10.1109\/CVPR.2015.7299067","key":"13430_CR5","DOI":"10.1109\/CVPR.2015.7299067"},{"key":"13430_CR6","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","volume":"6","author":"J Canny","year":"1986","unstructured":"Canny J (1986) A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on 6:679\u2013698. https:\/\/doi.org\/10.1109\/TPAMI.1986.4767851","journal-title":"Pattern Analysis and Machine Intelligence, IEEE Transactions on"},{"key":"13430_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TMM.2020.2987685","volume":"99","author":"YJ Cao","year":"2020","unstructured":"Cao YJ, Lin C, Li YJ (2020) Learning crisp boundaries using deep refinement network and adaptive weighting loss. IEEE Transactions on Multimedia PP 99:1\u20131. https:\/\/doi.org\/10.1109\/TMM.2020.2987685","journal-title":"IEEE Transactions on Multimedia PP"},{"issue":"1","key":"13430_CR8","doi-asserted-by":"publisher","first-page":"18","DOI":"10.2174\/2213275911666180821092033","volume":"12","author":"CL Chowdhary","year":"2019","unstructured":"Chowdhary CL (2019) 3D object recognition system based on local shape descriptors and depth data analysis. Recent Patents on Computer Science 12(1):18\u201324. https:\/\/doi.org\/10.2174\/2213275911666180821092033","journal-title":"Recent Patents on Computer Science"},{"issue":"4","key":"13430_CR9","doi-asserted-by":"publisher","first-page":"691","DOI":"10.1109\/CVPR.2017.622","volume":"22","author":"CL Chowdhary","year":"2019","unstructured":"Chowdhary CL, Goyal A, Vasnani BK (2019) Experimental assessment of beam search algorithm for improvement in image caption generation. Journal of Applied Science and Engineering 22(4):691\u2013698. https:\/\/doi.org\/10.1109\/CVPR.2017.622","journal-title":"Journal of Applied Science and Engineering"},{"issue":"8","key":"13430_CR10","doi-asserted-by":"publisher","first-page":"1558","DOI":"10.1109\/TPAMI.2014.2377715","volume":"37","author":"P Doll\u00e1r","year":"2014","unstructured":"Doll\u00e1r P, Zitnick CL (2014) Fast edge detection using structured forests. IEEE Trans Pattern Anal Mach Intell 37(8):1558\u20131570. https:\/\/doi.org\/10.1109\/TPAMI.2014.2377715","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"publisher","unstructured":"Gao L, Zhou Z, Shen H T, and Song J (2020) Bottom-up and top-down: bidirectional additive net for edge detection. Proceedings of the twenty-ninth international joint conference on artificial intelligence, IJCAI 2020 [scheduled for July 2020, Yokohama, Japan, postponed due to the Corona pandemic], pp 594-600. https:\/\/doi.org\/10.24963\/ijcai.2020\/83","key":"13430_CR11","DOI":"10.24963\/ijcai.2020\/83"},{"issue":"7","key":"13430_CR12","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1109\/TIP.2003.814250","volume":"12","author":"C Grigorescu","year":"2003","unstructured":"Grigorescu C, Petkov N, Westenberg MA (2003) Contour detection based on nonclassical receptive field inhibition. Image Processing, IEEE Transactions on 12(7):729\u2013739. https:\/\/doi.org\/10.1109\/TIP.2003.814250","journal-title":"Image Processing, IEEE Transactions on"},{"doi-asserted-by":"publisher","unstructured":"Gupta S, Arbelaez P, and Malik J (2013) Perceptual organization and recognition of indoor scenes from RGB-D images. Proceedings of the IEEE conference on computer vision and pattern recognition, pp 564-571. https:\/\/doi.org\/10.1109\/CVPR.2013.79","key":"13430_CR13","DOI":"10.1109\/CVPR.2013.79"},{"doi-asserted-by":"publisher","unstructured":"Gupta S, Girshick R, Arbel\u00e1ez P, Malik J (2014) Learning rich features from RGB-D images for object detection and segmentation. European Conference on Computer Vision:345\u2013360. https:\/\/doi.org\/10.1007\/978-3-319-10584-0_23","key":"13430_CR14","DOI":"10.1007\/978-3-319-10584-0_23"},{"doi-asserted-by":"publisher","unstructured":"Hallman S and Fowlkes C C (2015) Oriented edge forests for boundary detection. Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1732-1740. https:\/\/doi.org\/10.1109\/CVPR.2015.7298782","key":"13430_CR15","DOI":"10.1109\/CVPR.2015.7298782"},{"doi-asserted-by":"publisher","unstructured":"Isola P, Zoran D, Krishnan D, Adelson EH (2014) Crisp boundary detection using pointwise mutual information. European Conference on Computer Vision, pp:799\u2013814. https:\/\/doi.org\/10.1007\/978-3-319-10578-9_52","key":"13430_CR16","DOI":"10.1007\/978-3-319-10578-9_52"},{"doi-asserted-by":"publisher","unstructured":"Joachims T (1998) Text categorization with support vector machines: learning with many relevant features. Proc conference on Machine Learning, pp 137\u2013142. https:\/\/doi.org\/10.1007\/BFb0026683","key":"13430_CR17","DOI":"10.1007\/BFb0026683"},{"key":"13430_CR18","doi-asserted-by":"publisher","first-page":"II","DOI":"10.1109\/ISCAS.2004.1329421","volume":"2","author":"N Kazakova","year":"2004","unstructured":"Kazakova N, Margala M, Durdle NG (2004) Sobel edge detection processor for a real-time volume rendering system. Int Symp Circuits Sys 2:II\u2013913. https:\/\/doi.org\/10.1109\/ISCAS.2004.1329421","journal-title":"Int Symp Circuits Sys"},{"key":"13430_CR19","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.neucom.2020.06.069","volume":"409","author":"C Lin","year":"2020","unstructured":"Lin C, Cui L, Li F, Cao Y (2020) Lateral refinement network for contour detection. Neurocomputing 409:361\u2013371. https:\/\/doi.org\/10.1016\/j.neucom.2020.06.069","journal-title":"Neurocomputing"},{"doi-asserted-by":"publisher","unstructured":"Liu Y, Cheng M-M, Hu X, Wang K, and Bai X (2017) Richer convolutional features for edge detection. Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3000-3009. https:\/\/doi.org\/10.1109\/CVPR.2017.622","key":"13430_CR20","DOI":"10.1109\/CVPR.2017.622"},{"doi-asserted-by":"publisher","unstructured":"Maninis K-K, Pont-Tuset J, Arbel\u00e1ez P, and Van Gool L (2017) Convolutional oriented boundaries: from image segmentation to high-level tasks. arXiv preprint arXiv:1701.04658 40 (4): 819-833. https:\/\/doi.org\/10.1109\/TPAMI.2017.2700300","key":"13430_CR21","DOI":"10.1109\/TPAMI.2017.2700300"},{"issue":"5","key":"13430_CR22","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/TPAMI.2004.1273918","volume":"26","author":"DR Martin","year":"2004","unstructured":"Martin DR, Fowlkes CC, Malik J (2004) Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans Pattern Anal Mach Intell 26(5):530\u2013549. https:\/\/doi.org\/10.1109\/TPAMI.2004.1273918","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"publisher","unstructured":"Mottaghi R, Chen X, Liu X, Cho NG, Yuille A (2013) The role of context for object detection and semantic segmentation in the wild. Comput Vis Pattern Recognit. https:\/\/doi.org\/10.13140\/2.1.2577.6000","key":"13430_CR23","DOI":"10.13140\/2.1.2577.6000"},{"doi-asserted-by":"publisher","unstructured":"Seif A, Salut MM, Marsono MN (2010) A hardware architecture of Prewitt edge detection. Sustain Utilization Dev Eng Technol:99\u2013101. https:\/\/doi.org\/10.1109\/STUDENT.2010.5686999","key":"13430_CR24","DOI":"10.1109\/STUDENT.2010.5686999"},{"doi-asserted-by":"publisher","unstructured":"Shen W, Wang X, Wang Y, Bai X, and Zhang Z (2015) Deepcontour: a deep convolutional feature learned by positive-sharing loss for contour detection. Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3982-3991. https:\/\/doi.org\/10.1109\/CVPR.2015.7299024","key":"13430_CR25","DOI":"10.1109\/CVPR.2015.7299024"},{"doi-asserted-by":"crossref","unstructured":"Silberman N, Hoiem D, Kohli P, Fergus R (2012) Indoor segmentation and support inference from rgbd images. European conference on computer vision, pp:746\u2013760","key":"13430_CR26","DOI":"10.1007\/978-3-642-33715-4_54"},{"doi-asserted-by":"publisher","unstructured":"Tu Z (2005) Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering. IEEE international conference on computer vision, pp 1589-1596. https:\/\/doi.org\/10.1109\/ICCV.2005.194","key":"13430_CR27","DOI":"10.1109\/ICCV.2005.194"},{"key":"13430_CR28","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/B978-0-444-87137-4.50011-4","volume":"7","author":"LJV Vliet","year":"1988","unstructured":"Vliet LJV, Young IT, Beckers GL (1988) An edge detection model based on non-linear Laplace filtering. Machine Intelligence and Pattern Recognition 7:63\u201373. https:\/\/doi.org\/10.1016\/B978-0-444-87137-4.50011-4","journal-title":"Machine Intelligence and Pattern Recognition"},{"doi-asserted-by":"publisher","unstructured":"Wang Y, Zhao X, Huang K (2017) Deep crisp boundaries. IEEE Conference on Computer Vision & Pattern Recognition, pp:3892\u20133900. https:\/\/doi.org\/10.1109\/CVPR.2017.187","key":"13430_CR29","DOI":"10.1109\/CVPR.2017.187"},{"unstructured":"Xiaofeng R, Bo L (2012) Discriminatively trained sparse code gradients for contour detection. Adv Neural Inf Process Syst 584\u2013592. https:\/\/dl.acm.org\/doi\/10.5555\/2999134.2999200","key":"13430_CR30"},{"doi-asserted-by":"publisher","unstructured":"Xie S and Tu Z (2015) Holistically-nested edge detection. Proceedings of the IEEE international conference on computer vision, pp 1395-1403. https:\/\/doi.org\/10.1007\/s11263-017-1004-z","key":"13430_CR31","DOI":"10.1007\/s11263-017-1004-z"},{"doi-asserted-by":"publisher","unstructured":"Yu Z, Feng C, Liu M Y, and Ramalingam S (2017) CASENet: deep category-aware semantic edge detection. Computer Vision & Pattern Recognition, pp 5964-5973. https:\/\/doi.org\/10.1109\/CVPR.2017.191","key":"13430_CR32","DOI":"10.1109\/CVPR.2017.191"},{"doi-asserted-by":"publisher","unstructured":"Zhang R, You M (2020) Fast contour detection with supervised attention learning. J Real-Time Image Proc:1\u201311. https:\/\/doi.org\/10.1007\/s11554-020-00980-1","key":"13430_CR33","DOI":"10.1007\/s11554-020-00980-1"},{"doi-asserted-by":"publisher","unstructured":"Zhang Z, Xing F, Shi X, Yang L (2016) SemiContour: a semi-supervised learning approach for contour detection. Computer vision and pattern recognition, vol. 2016, pp 251-259. 2016:251\u2013259. https:\/\/doi.org\/10.1109\/CVPR.2016.34","key":"13430_CR34","DOI":"10.1109\/CVPR.2016.34"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13430-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13430-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13430-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,4]],"date-time":"2023-01-04T09:41:41Z","timestamp":1672825301000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13430-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":34,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["13430"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13430-w","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2022,7,18]]},"assertion":[{"value":"8 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 July 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}