{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:03:15Z","timestamp":1775066595561,"version":"3.50.1"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T00:00:00Z","timestamp":1701907200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T00:00:00Z","timestamp":1701907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Innovation Capability Support Program of Shaanxi","award":["No.2021TD-29"],"award-info":[{"award-number":["No.2021TD-29"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.62176204"],"award-info":[{"award-number":["No.62176204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Research and Development Plan of Shaanxi Province","award":["No.2022GY-066"],"award-info":[{"award-number":["No.2022GY-066"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17706-7","type":"journal-article","created":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T06:02:07Z","timestamp":1701928927000},"page":"54657-54672","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An exclusive U-net for fine and crisp edge detection"],"prefix":"10.1007","volume":"83","author":[{"given":"Ying","family":"An","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6646-3698","authenticated-orcid":false,"given":"Junfeng","family":"Jing","sequence":"additional","affiliation":[]},{"given":"Xuewei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jiaqi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Junmin","family":"Bao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,7]]},"reference":[{"issue":"13","key":"17706_CR1","doi-asserted-by":"publisher","first-page":"9543","DOI":"10.1007\/s11042-019-08035-9","volume":"79","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Zhang M, Cui Y, Zhang D (2020) Detection and tracking of human track and field motion targets based on deep learning. Multimedia Tools Appl 79(13):9543\u20139563","journal-title":"Multimedia Tools Appl"},{"issue":"19","key":"17706_CR2","doi-asserted-by":"publisher","first-page":"29177","DOI":"10.1007\/s11042-021-10959-0","volume":"80","author":"JB Florindo","year":"2021","unstructured":"Florindo JB (2021) Reorganizing local image features with chaotic maps: an application to texture recognition. Multimedia Tools Appl 80(19):29177\u201329197","journal-title":"Multimedia Tools Appl"},{"key":"17706_CR3","doi-asserted-by":"crossref","unstructured":"Rao S (2021) A framework for robust motion estimation and segmentation in adverse outdoor conditions. Multimedia Tools Appl 1\u201321","DOI":"10.1007\/s11042-021-11502-x"},{"issue":"6","key":"17706_CR4","doi-asserted-by":"publisher","first-page":"921","DOI":"10.3390\/sym13060921","volume":"13","author":"R Wang","year":"2021","unstructured":"Wang R, Wu G, Wang Q, Yuan L, Zhang Z, Miao G (2021) Reversible data hiding in encrypted images using median edge detector and two\u2019s complement. Symmetry 13(6):921","journal-title":"Symmetry"},{"key":"17706_CR5","first-page":"3373","volume":"12","author":"S Jeevitha","year":"2021","unstructured":"Jeevitha S, Amutha Prabha N (2021) Novel medical image encryption using dwt block-based scrambling and edge maps J Ambient Intell Human Comput 12:3373\u20133388","journal-title":"Novel medical image encryption using dwt block-based scrambling and edge maps J Ambient Intell Human Comput"},{"issue":"5","key":"17706_CR6","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1109\/TPAMI.2010.161","volume":"33","author":"P Arbelaez","year":"2010","unstructured":"Arbelaez P, Maire M, Fowlkes C, Malik J (2010) Contour detection and hierarchical image segmentation. IEEE Trans Pattern Ana Mach Intell 33(5):898\u2013916","journal-title":"IEEE Trans Pattern Ana Mach Intell"},{"key":"17706_CR7","doi-asserted-by":"crossref","unstructured":"Xie S, Tu Z (2015) Holistically-nested edge detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1395\u20131403","DOI":"10.1109\/ICCV.2015.164"},{"key":"17706_CR8","doi-asserted-by":"crossref","unstructured":"Deng R, Shen C, Liu S, Wang H, Liu X (2018) Learning to predict crisp boundaries. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 562\u2013578","DOI":"10.1007\/978-3-030-01231-1_35"},{"issue":"3","key":"17706_CR9","doi-asserted-by":"publisher","first-page":"297","DOI":"10.2307\/1932409","volume":"26","author":"LR Dice","year":"1945","unstructured":"Dice LR (1945) Measures of the amount of ecologic association between species. Ecol 26(3):297\u2013302","journal-title":"Ecol"},{"key":"17706_CR10","doi-asserted-by":"crossref","unstructured":"Wang Y, Zhao X, Huang K (2017) Deep crisp boundaries. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3892\u20133900","DOI":"10.1109\/CVPR.2017.187"},{"key":"17706_CR11","doi-asserted-by":"crossref","unstructured":"Huan L, Xue N, Zheng X, He W, Gong J, Xia G-S (2021) Unmixing convolutional features for crisp edge detection. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2021.3084197"},{"key":"17706_CR12","unstructured":"Poma XS, Riba E, Sappa A (2020) Dense extreme inception network: Towards a robust cnn model for edge detection. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 1923\u20131932"},{"key":"17706_CR13","doi-asserted-by":"crossref","unstructured":"Liu Y, Cheng M-M, Hu X, Wang K, Bai X (2017) Richer convolutional features for edge detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3000\u20133009","DOI":"10.1109\/CVPR.2017.622"},{"key":"17706_CR14","doi-asserted-by":"crossref","unstructured":"He J, Zhang S, Yang M, Shan Y, Huang T (2019) Bi-directional cascade network for perceptual edge detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3828\u20133837","DOI":"10.1109\/CVPR.2019.00395"},{"key":"17706_CR15","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/s11390-017-1764-5","volume":"33","author":"K Li","year":"2018","unstructured":"Li K, He F-Z, Yu H-P (2018) Robust visual tracking based on convolutional features with illumination and occlusion handing. J Comput Sci Technol 33:223\u2013236","journal-title":"J Comput Sci Technol"},{"key":"17706_CR16","doi-asserted-by":"crossref","unstructured":"Mottaghi R, Chen X, Liu X, Cho N-G, Lee S-W, Fidler S, Urtasun R, Yuille A (2014) The role of context for object detection and semantic segmentation in the wild In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 891\u2013898","DOI":"10.1109\/CVPR.2014.119"},{"key":"17706_CR17","doi-asserted-by":"crossref","unstructured":"Silberman N, Hoiem D, Kohli P, Fergus R (2012) Indoor segmentation and support inference from rgbd images. In: European Conference on Computer Vision, pp. 746\u2013760","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"17706_CR18","doi-asserted-by":"crossref","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation. In: International Conference on Medical Image Computing and Computer-assisted Intervention pp. 234\u2013241, Springer","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"19","key":"17706_CR19","doi-asserted-by":"publisher","first-page":"29965","DOI":"10.1007\/s11042-021-11187-2","volume":"80","author":"SK Mishra","year":"2021","unstructured":"Mishra SK, Singh KK, Dixit R, Bajpai MK (2021) Design of fractional calculus based differentiator for edge detection in color images. Multimedia Tools Appl 80(19):29965\u201329983","journal-title":"Multimedia Tools Appl"},{"key":"17706_CR20","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. IEEE Trans Pattern Analysis Mach Intell 6:679\u2013698","journal-title":"IEEE Trans Pattern Analysis Mach Intell"},{"issue":"1167","key":"17706_CR21","first-page":"187","volume":"207","author":"D Marr","year":"1980","unstructured":"Marr D, Hildreth E (1980) Theory of edge detection. Proc R Soc Lond Ser B Biol Sci 207(1167):187\u2013217","journal-title":"Proc R Soc Lond Ser B Biol Sci"},{"issue":"8","key":"17706_CR22","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","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"17706_CR23","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","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"17706_CR24","doi-asserted-by":"crossref","unstructured":"Lim JJ, Zitnick CL, Doll\u00e1r P (2013) Sketch tokens: A learned mid-level representation for contour and object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3158\u20133165","DOI":"10.1109\/CVPR.2013.406"},{"key":"17706_CR25","doi-asserted-by":"crossref","unstructured":"Bertasius G, Shi J, Torresani L (2015) Deepedge: A multi-scale bifurcated deep network for top-down contour detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition pp. 4380\u20134389","DOI":"10.1109\/CVPR.2015.7299067"},{"key":"17706_CR26","unstructured":"Shen W, Wang X, Wang Y, Bai X, Zhang Z (2015) Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition pp. 3982\u20133991"},{"key":"17706_CR27","doi-asserted-by":"crossref","unstructured":"Ganin Y, Lempitsky V (2014) N4-fields: Neural network nearest neighbor fields for image transforms. In: Asian Conference on Computer Vision, pp. 536\u2013551, Springer","DOI":"10.1007\/978-3-319-16808-1_36"},{"key":"17706_CR28","doi-asserted-by":"crossref","unstructured":"Bertasius G, Shi J, Torresani L (2015) High-for-low and low-for-high: Efficient boundary detection from deep object features and its applications to high-level vision. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 504\u2013512","DOI":"10.1109\/ICCV.2015.65"},{"issue":"1","key":"17706_CR29","doi-asserted-by":"publisher","first-page":"1611","DOI":"10.1007\/s11042-020-09800-x","volume":"80","author":"T Fang","year":"2021","unstructured":"Fang T, Zhang M, Fan Y, Wu W, Gan H, She Q (2021) Developing a feature decoder network with low-to-high hierarchies to improve edge detection. Multimedia Tools Appl 80(1):1611\u20131624","journal-title":"Multimedia Tools Appl"},{"key":"17706_CR30","doi-asserted-by":"crossref","unstructured":"Yang J, Price B, Cohen S, Lee H, Yang M-H (2016) Object contour detection with a fully convolutional encoder-decoder network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 193\u2013202","DOI":"10.1109\/CVPR.2016.28"},{"key":"17706_CR31","doi-asserted-by":"crossref","unstructured":"Liu Y, Lew MS (2016) Learning relaxed deep supervision for better edge detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 231\u2013240","DOI":"10.1109\/CVPR.2016.32"},{"key":"17706_CR32","doi-asserted-by":"crossref","unstructured":"Su Z, Liu W, Yu Z, Hu D, Liao Q, Tian Q, Pietik\u00e4inen M, Liu L (2021) Pixel difference networks for efficient edge detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5117\u20135127","DOI":"10.1109\/ICCV48922.2021.00507"},{"key":"17706_CR33","doi-asserted-by":"crossref","unstructured":"Pu M, Huang Y, Liu Y, Guan Q, Ling H (2022) Edter: Edge detection with transformer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1402\u20131412","DOI":"10.1109\/CVPR52688.2022.00146"},{"issue":"1","key":"17706_CR34","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/s11263-021-01539-8","volume":"130","author":"Y Liu","year":"2022","unstructured":"Liu Y, Cheng M-M, Fan D-P, Zhang L, Bian J-W, Tao D (2022) Semantic edge detection with diverse deep supervision. Inter J Comput Vision 130(1):179\u2013198","journal-title":"Inter J Comput Vision"},{"key":"17706_CR35","doi-asserted-by":"publisher","first-page":"26282","DOI":"10.1109\/ACCESS.2022.3146339","volume":"10","author":"S-S Bao","year":"2022","unstructured":"Bao S-S, Huang Y-R, Xu G-Y (2022) Bidirectional multiscale refinement network for crisp edge detection. IEEE Access 10:26282\u201326293","journal-title":"IEEE Access"},{"issue":"7","key":"17706_CR36","doi-asserted-by":"publisher","first-page":"1635","DOI":"10.1007\/s11760-021-01899-1","volume":"15","author":"Y Wang","year":"2021","unstructured":"Wang Y, Wang L, Qiu J, Yang Y (2021) Feature enhancement: predict more detailed and crisper edges. Sig, Image Video Process 15(7):1635\u20131642","journal-title":"Sig, Image Video Process"},{"key":"17706_CR37","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee J-Y, Kweon IS (2018) Cbam: Convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"issue":"12","key":"17706_CR38","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1007\/s11263-017-1035-5","volume":"126","author":"A Akbarinia","year":"2018","unstructured":"Akbarinia A, Parraga CA (2018) Feedback and surround modulated boundary detection. Inter J Comput Vision 126(12):1367\u20131380","journal-title":"Inter J Comput Vision"},{"key":"17706_CR39","unstructured":"Kokkinos I (2015) Pushing the boundaries of boundary detection using deep learning. arXiv:1511.07386"},{"key":"17706_CR40","unstructured":"Xiaofeng R, Bo L (2012) Discriminatively trained sparse code gradients for contour detection. Adv Neural Inf Proce Syst 25"},{"key":"17706_CR41","doi-asserted-by":"crossref","unstructured":"Gupta S, Arbelaez P, Malik J (2013) Perceptual organization and recognition of indoor scenes from rgb-d images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition pp. 564\u2013571","DOI":"10.1109\/CVPR.2013.79"},{"key":"17706_CR42","doi-asserted-by":"crossref","unstructured":"Hallman S, Fowlkes CC (2015) Oriented edge forests for boundary detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1732\u20131740","DOI":"10.1109\/CVPR.2015.7298782"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17706-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17706-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17706-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T10:45:03Z","timestamp":1715769903000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17706-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,7]]},"references-count":42,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["17706"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17706-7","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,7]]},"assertion":[{"value":"6 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 December 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors declared no potential conflicts of interest with respect to the research, author-ship, and publication of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interests"}}]}}