{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T22:20:03Z","timestamp":1758925203014,"version":"3.37.3"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T00:00:00Z","timestamp":1610409600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T00:00:00Z","timestamp":1610409600000},"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":["Appl Intell"],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1007\/s10489-020-02114-3","type":"journal-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T21:28:55Z","timestamp":1610486935000},"page":"5610-5621","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Adaptive fusion with multi-scale features for interactive image segmentation"],"prefix":"10.1007","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7308-5453","authenticated-orcid":false,"given":"Zongyuan","family":"Ding","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quansen","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,12]]},"reference":[{"key":"2114_CR1","doi-asserted-by":"crossref","unstructured":"Kang W, Yang Q, Liang R (2009) The comparative research on image segmentation algorithms. In: International Workshop on Education Technology and Computer Science. pp 703\u2013707","DOI":"10.1109\/ETCS.2009.417"},{"key":"2114_CR2","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.neucom.2015.08.125","volume":"204","author":"Y Xia","year":"2016","unstructured":"Xia Y, Ji Z, Zhang Y (2016) Brain MRI image segmentation based on learning local variational Gaussian mixture models. Neurocomputing 204:189\u2013197","journal-title":"Neurocomputing"},{"key":"2114_CR3","doi-asserted-by":"crossref","unstructured":"Ghosh S, Das N, Das I, Maulik U (2019) Understanding deep learning techniques for image segmentation.\u00a0ACM Computing Surveys (CSUR) 52(4):1\u201335","DOI":"10.1145\/3329784"},{"key":"2114_CR4","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","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"2114_CR5","doi-asserted-by":"crossref","unstructured":"Shelhamer E, Long J, Darrell T (2017) Fully Convolutional Networks for Semantic Segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp 3431\u20133440","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"2114_CR6","doi-asserted-by":"crossref","unstructured":"Bai X, Sapiro G A (2007) Geodesic framework for fast interactive image and video segmentation and matting. In: 2007 IEEE 11th International Conference on Computer Vision. pp 1\u20138","DOI":"10.1109\/ICCV.2007.4408931"},{"key":"2114_CR7","unstructured":"Boykov YY, Jolly M-P (2001) Interactive graph cuts for optimal boundary & region segmentation of objects in ND images. In: Proceedings 8th IEEE international conference on computer vision. pp 105\u2013112"},{"issue":"2","key":"2114_CR8","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s11263-006-8711-1","volume":"72","author":"D Cremers","year":"2007","unstructured":"Cremers D, Rousson M, Deriche R (2007) A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape. Int J Comput Vis 72(2):195\u2013215","journal-title":"Int J Comput Vis"},{"key":"2114_CR9","doi-asserted-by":"publisher","first-page":"1768","DOI":"10.1109\/TPAMI.2006.233","volume":"28","author":"L Grady","year":"2006","unstructured":"Grady L (2006) Random walks for image segmentation. IEEE Trans Pattern Anal Mach Intell 28:1768\u20131783","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"2114_CR10","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1006\/gmip.1998.0480","volume":"60","author":"EN Mortensen","year":"1998","unstructured":"Mortensen EN, Barrett WA (1998) Interactive segmentation with intelligent scissors. Graph Model Image Process 60(5):349\u2013384","journal-title":"Graph Model Image Process"},{"issue":"5","key":"2114_CR11","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1109\/34.1000236","volume":"24","author":"D Comaniciu","year":"2002","unstructured":"Comaniciu D, Meer P (2002) Mean shift: a robust approach toward feature space analysis. IEEE Trans Pattern Anal Mach Intell 24(5):603\u2013619","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"2114_CR12","doi-asserted-by":"publisher","first-page":"1659","DOI":"10.1016\/j.asoc.2012.02.010","volume":"12","author":"Z Ji","year":"2012","unstructured":"Ji Z, Xia Y, Chen Q, Sun Q, Xia D, Feng DD (2012) Fuzzy c-means clustering with weighted image patch for image segmentation. Appl Soft Comput 12(6):1659\u20131667","journal-title":"Appl Soft Comput"},{"issue":"3","key":"2114_CR13","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1145\/1015706.1015720","volume":"23","author":"C Rother","year":"2004","unstructured":"Rother C, Kolmogorov V, Blake A (2004) \" GrabCut\" interactive foreground extraction using iterated graph cuts. ACM Trans Graph (TOG) 23(3):309\u2013314","journal-title":"ACM Trans Graph (TOG)"},{"key":"2114_CR14","doi-asserted-by":"crossref","unstructured":"Freedman D, Zhang T (2005) Interactive graph cut based segmentation with shape priors. In: 2005 IEEE computer society conference on computer vision and pattern recognition. pp 755\u2013762","DOI":"10.1109\/CVPR.2005.191"},{"issue":"4","key":"2114_CR15","doi-asserted-by":"publisher","first-page":"1451","DOI":"10.1109\/TIP.2014.2302892","volume":"23","author":"J Shen","year":"2014","unstructured":"Shen J, Du Y, Wang W, Li X (2014) Lazy random walks for superpixel segmentation. IEEE Trans Image Process 23(4):1451\u20131462","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"2114_CR16","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1145\/1015706.1015719","volume":"23","author":"Y Li","year":"2004","unstructured":"Li Y, Sun J, Tang C-K, Shum H-Y (2004) Lazy snapping. ACM Trans Graph (ToG) 23(3):303\u2013308","journal-title":"ACM Trans Graph (ToG)"},{"issue":"12","key":"2114_CR17","doi-asserted-by":"publisher","first-page":"2358","DOI":"10.1109\/TMM.2016.2600441","volume":"18","author":"T Wang","year":"2016","unstructured":"Wang T, Ji Z, Sun Q, Chen Q, Jing X-Y (2016) Interactive multilabel image segmentation via robust multilayer graph constraints. IEEE Trans Multimed 18(12):2358\u20132371","journal-title":"IEEE Trans Multimed"},{"key":"2114_CR18","doi-asserted-by":"crossref","unstructured":"Kim TH, Lee KM, Lee SU (2010) Nonparametric higher-order learning for interactive segmentation. In: 2010 IEEE computer society conference on computer vision and pattern recognition. pp 3201\u20133208","DOI":"10.1109\/CVPR.2010.5540078"},{"issue":"8","key":"2114_CR19","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi J, Malik J (2000) Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22(8):888\u2013905","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"2114_CR20","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, S\u00fcsstrunk S (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2114_CR21","doi-asserted-by":"crossref","unstructured":"Kallel I K, Almouahed S, Solaiman B, Boss\u00e9 \u00c9 (2018) An iterative possibilistic knowledge diffusion approach for blind medical image segmentation.\u00a0Pattern Recognit 78:182\u2013197","DOI":"10.1016\/j.patcog.2018.01.024"},{"issue":"1","key":"2114_CR22","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/TPAMI.2012.60","volume":"35","author":"X Yang","year":"2012","unstructured":"Yang X, Prasad L, Latecki LJ (2012) Affinity learning with diffusion on tensor product graph. IEEE Trans Pattern Anal Mach Intell 35(1):28\u201338","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2114_CR23","doi-asserted-by":"crossref","unstructured":"Wang B, Tu Z (2012) Affinity learning via self-diffusion for image segmentation and clustering. In: 2012 IEEE conference on computer vision and pattern recognition. pp 2312\u20132319","DOI":"10.1109\/CVPR.2012.6247942"},{"key":"2114_CR24","doi-asserted-by":"crossref","unstructured":"Donoser M, Bischof H (2013) Diffusion processes for retrieval revisited. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp 1320\u20131327","DOI":"10.1109\/CVPR.2013.174"},{"issue":"5","key":"2114_CR25","first-page":"861","volume":"32","author":"X Bai","year":"2009","unstructured":"Bai X, Yang X, Latecki LJ, Liu W, Tu Z (2009) Learning context-sensitive shape similarity by graph transduction. IEEE Trans Pattern Anal Mach Intell 32(5):861\u2013874","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"2114_CR26","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1109\/TIP.2015.2505184","volume":"25","author":"X Dong","year":"2015","unstructured":"Dong X, Shen J, Shao L, Van Gool L (2015) Sub-Markov random walk for image segmentation. IEEE Trans Image Process 25(2):516\u2013527","journal-title":"IEEE Trans Image Process"},{"key":"2114_CR27","doi-asserted-by":"crossref","unstructured":"Casaca W, Gustavo Nonato L, Taubin G (2014) Laplacian coordinates for seeded image segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp 384\u2013391","DOI":"10.1109\/CVPR.2014.56"},{"issue":"1","key":"2114_CR28","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1109\/TIP.2016.2621663","volume":"26","author":"CG Bampis","year":"2016","unstructured":"Bampis CG, Maragos P, Bovik AC (2016) Graph-driven diffusion and random walk schemes for image segmentation. IEEE Trans Image Process 26(1):35\u201350","journal-title":"IEEE Trans Image Process"},{"key":"2114_CR29","doi-asserted-by":"crossref","unstructured":"Pedronette DCG, Torres RdS (2016) Rank diffusion for context-based image retrieval. In: Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval. pp 321\u2013325","DOI":"10.1145\/2911996.2912060"},{"issue":"5","key":"2114_CR30","doi-asserted-by":"publisher","first-page":"1174","DOI":"10.1109\/TMM.2013.2242450","volume":"15","author":"L Luo","year":"2013","unstructured":"Luo L, Shen C, Zhang C, van den Hengel A (2013) Shape similarity analysis by self-tuning locally constrained mixed-diffusion. IEEE Trans Multimed 15(5):1174\u20131183","journal-title":"IEEE Trans Multimed"},{"issue":"1","key":"2114_CR31","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1109\/TIP.2018.2863028","volume":"28","author":"S Bai","year":"2018","unstructured":"Bai S, Zhou Z, Wang J, Bai X, Latecki LJ, Tian Q (2018) Automatic ensemble diffusion for 3d shape and image retrieval. IEEE Trans Image Process 28(1):88\u2013101","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"2114_CR32","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1109\/3477.764879","volume":"29","author":"K Krishna","year":"1999","unstructured":"Krishna K, Murty MN (1999) Genetic K-means algorithm. IEEE Trans Syst Man Cybern Part B (Cybern) 29(3):433\u2013439","journal-title":"IEEE Trans Syst Man Cybern Part B (Cybern)"},{"issue":"1","key":"2114_CR33","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1109\/TIP.2018.2867941","volume":"28","author":"T Wang","year":"2018","unstructured":"Wang T, Yang J, Ji Z, Sun Q (2018) Probabilistic diffusion for interactive image segmentation. IEEE Trans Image Process 28(1):330\u2013342","journal-title":"IEEE Trans Image Process"},{"key":"2114_CR34","unstructured":"Yang Q, Li C, Guo J (2019) Multi-order information for working set selection of sequential minimal optimization. In: the 22nd International Conference on Artificial Intelligence and Statistics.\u00a0pp 3264\u20133272"},{"key":"2114_CR35","doi-asserted-by":"crossref","unstructured":"Santner J, Pock T, Bischof H (2010) Interactive multi-label segmentation. In: Asian conference on computer vision. pp 397\u2013410","DOI":"10.1007\/978-3-642-19315-6_31"},{"key":"2114_CR36","doi-asserted-by":"crossref","unstructured":"Yao B, Yang X, Zhu S-C (2007) Introduction to a large-scale general purpose ground truth database: methodology, annotation tool and benchmarks. In: International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition. pp 169\u2013183","DOI":"10.1007\/978-3-540-74198-5_14"},{"key":"2114_CR37","doi-asserted-by":"crossref","unstructured":"Meil\u01ce M (2005) Comparing clusterings: an axiomatic view. In:\u00a0Proceedings of the 22nd international conference on Machine learning.\u00a0pp 577\u2013584","DOI":"10.1145\/1102351.1102424"},{"key":"2114_CR38","doi-asserted-by":"crossref","unstructured":"Jang W, Kim C (2019) Interactive Image Segmentation via Backpropagating Refinement Scheme. Comput Vis Pattern Recognit 5297\u20135306","DOI":"10.1109\/CVPR.2019.00544"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-02114-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-020-02114-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-020-02114-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T04:40:54Z","timestamp":1625805654000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-020-02114-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,12]]},"references-count":38,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["2114"],"URL":"https:\/\/doi.org\/10.1007\/s10489-020-02114-3","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2021,1,12]]},"assertion":[{"value":"2 December 2020","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}