{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:17:50Z","timestamp":1772907470134,"version":"3.50.1"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"24","license":[{"start":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T00:00:00Z","timestamp":1684540800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T00:00:00Z","timestamp":1684540800000},"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":["62171315"],"award-info":[{"award-number":["62171315"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s00521-023-08640-8","type":"journal-article","created":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T11:02:06Z","timestamp":1684580526000},"page":"17733-17747","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Transformer guidance dual-stream network for salient object detection in optical remote sensing images"],"prefix":"10.1007","volume":"35","author":[{"given":"Yi","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3130-1685","authenticated-orcid":false,"given":"Jichang","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huihui","family":"Yue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangjun","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sida","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,5,20]]},"reference":[{"issue":"11","key":"8640_CR1","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254\u20131259","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"8640_CR2","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/s41095-019-0149-9","volume":"5","author":"A Borji","year":"2019","unstructured":"Borji A, Cheng M-M, Hou Q, Jiang H, Li J (2019) Salient object detection: a survey. Comput Visual Media 5(2):117\u2013150","journal-title":"Comput Visual Media"},{"issue":"13","key":"8640_CR3","doi-asserted-by":"publisher","first-page":"8811","DOI":"10.1007\/s00521-019-04352-0","volume":"32","author":"IS Mohamed","year":"2020","unstructured":"Mohamed IS, Capitanelli A, Mastrogiovanni F, Rovetta S, Zaccaria R (2020) Detection, localisation and tracking of pallets using machine learning techniques and 2D range data. Neural Comput Appl 32(13):8811\u20138828","journal-title":"Neural Comput Appl"},{"key":"8640_CR4","doi-asserted-by":"crossref","unstructured":"Wang X, You S, Li X, Ma H (2018) Weakly-supervised semantic segmentation by iteratively mining common object features. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1354\u20131362","DOI":"10.1109\/CVPR.2018.00147"},{"issue":"04","key":"8640_CR5","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1109\/TPAMI.2018.2819173","volume":"41","author":"W Wang","year":"2019","unstructured":"Wang W, Shen J, Porikli F, Yang R (2019) Semi-supervised video object segmentation with super-trajectories. IEEE Trans Pattern Anal Mach Intell 41(04):985\u2013998","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8640_CR6","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.cviu.2017.10.001","volume":"163","author":"A Das","year":"2017","unstructured":"Das A, Agrawal H, Zitnick L, Parikh D, Batra D (2017) Human attention in visual question answering: do humans and deep networks look at the same regions? Comput Vis Image Underst 163:90\u2013100","journal-title":"Comput Vis Image Underst"},{"key":"8640_CR7","doi-asserted-by":"crossref","unstructured":"Fang H, Gupta S, Iandola F, Srivastava RK, Deng L, Doll\u00e1r P, Gao J, He X, Mitchell M, Platt JC et al (2015) From captions to visual concepts and back. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1473\u20131482","DOI":"10.1109\/CVPR.2015.7298754"},{"issue":"2","key":"8640_CR8","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/s00138-018-01000-w","volume":"30","author":"R Mechrez","year":"2019","unstructured":"Mechrez R, Shechtman E, Zelnik-Manor L (2019) Saliency driven image manipulation. Mach Vis Appl 30(2):189\u2013202","journal-title":"Mach Vis Appl"},{"key":"8640_CR9","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07617-3","author":"W Li","year":"2022","unstructured":"Li W, Zhu H, Yang S, Wang P, Zhang H (2022) GA-SRN: graph attention based text-image semantic reasoning network for fine-grained image classification and retrieval. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-022-07617-3","journal-title":"Neural Comput Appl"},{"key":"8640_CR10","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2020.3009243","author":"X Ma","year":"2020","unstructured":"Ma X, Zhao R, Shi Z (2020) Multiscale methods for optical remote-sensing image captioning. IEEE Geosci Remote Sens Lett. https:\/\/doi.org\/10.1109\/LGRS.2020.3009243","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"8640_CR11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3123666","author":"Y Han","year":"2021","unstructured":"Han Y, Yang X, Pu T, Peng Z (2021) Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images. IEEE Trans Geosci Remote Sens. https:\/\/doi.org\/10.1109\/TGRS.2021.3123666","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"8640_CR12","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1109\/TIP.2020.3042084","volume":"30","author":"Q Zhang","year":"2020","unstructured":"Zhang Q, Cong R, Li C, Cheng M-M, Fang Y, Cao X, Zhao Y, Kwong S (2020) Dense attention fluid network for salient object detection in optical remote sensing images. IEEE Trans Image Process 30:1305\u20131317","journal-title":"IEEE Trans Image Process"},{"key":"8640_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07915-w","author":"Q Yang","year":"2022","unstructured":"Yang Q, Zhou Y, Chai X, Zhang M, Zhang W, Wang J (2022) Exploring class-agnostic pixels for scribble-supervised high-resolution salient object detection. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-022-07915-w","journal-title":"Neural Comput Appl"},{"key":"8640_CR14","unstructured":"Mao Y, Zhang J, Wan Z, Dai Y, Li A, Lv Y, Tian X, Fan D-P, Barnes N (2021) Transformer transforms salient object detection and camouflaged object detection. arXiv preprint arXiv:2104.10127"},{"key":"8640_CR15","doi-asserted-by":"crossref","unstructured":"Liu Z, Wang Y, Tu Z, Xiao Y, Tang B (2021) TriTransNet: RGB-D salient object detection with a triplet transformer embedding network. In: Proceedings of the 29th ACM international conference on multimedia, pp 4481\u20134490","DOI":"10.1145\/3474085.3475601"},{"key":"8640_CR16","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. In: Advances in neural information processing systems, pp 5998\u20136008"},{"key":"8640_CR17","doi-asserted-by":"crossref","unstructured":"Khan S, Naseer M, Hayat M, Zamir SW, Khan FS, Shah M (2021) Transformers in vision: a survey. ACM Comput Surv (CSUR)","DOI":"10.1145\/3505244"},{"key":"8640_CR18","doi-asserted-by":"crossref","unstructured":"Pang Y, Zhao X, Zhang L, Lu H (2020) Multi-scale interactive network for salient object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9413\u20139422","DOI":"10.1109\/CVPR42600.2020.00943"},{"issue":"10","key":"8640_CR19","doi-asserted-by":"publisher","first-page":"7547","DOI":"10.1007\/s00521-021-06845-3","volume":"34","author":"T Chen","year":"2022","unstructured":"Chen T, Hu X, Xiao J, Zhang G, Wang S (2022) CFIDNet: cascaded feature interaction decoder for RGB-D salient object detection. Neural Comput Appl 34(10):7547\u20137563","journal-title":"Neural Comput Appl"},{"key":"8640_CR20","doi-asserted-by":"crossref","unstructured":"Zhao J-X, Liu J-J, Fan D-P, Cao Y, Yang J, Cheng M-M (2019) EGNet: edge guidance network for salient object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 8779\u20138788","DOI":"10.1109\/ICCV.2019.00887"},{"key":"8640_CR21","doi-asserted-by":"crossref","unstructured":"Liu J-J, Hou Q, Cheng M-M, Feng J, Jiang J (2019) A simple pooling-based design for real-time salient object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3917\u20133926","DOI":"10.1109\/CVPR.2019.00404"},{"key":"8640_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07330-1","author":"T Chen","year":"2022","unstructured":"Chen T, Xiao J, Hu X, Zhang G, Wang S (2022) Spatiotemporal context-aware network for video salient object detection. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-022-07330-1","journal-title":"Neural Comput Appl"},{"key":"8640_CR23","doi-asserted-by":"crossref","unstructured":"Su J, Li J, Zhang Y, Xia C, Tian Y (2019) Selectivity or invariance: boundary-aware salient object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 3799\u20133808","DOI":"10.1109\/ICCV.2019.00390"},{"key":"8640_CR24","doi-asserted-by":"crossref","unstructured":"Long J, Shelhamer E, Darrell T (2015) Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3431\u20133440","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"8640_CR25","doi-asserted-by":"crossref","unstructured":"Hou Q, Cheng M-M, Hu X, Borji A, Tu Z, Torr PH (2017) Deeply supervised salient object detection with short connections. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3203\u20133212","DOI":"10.1109\/CVPR.2017.563"},{"key":"8640_CR26","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":"8640_CR27","doi-asserted-by":"crossref","unstructured":"Liu N, Han J, Yang M-H (2018) Picanet: learning pixel-wise contextual attention for saliency detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3089\u20133098","DOI":"10.1109\/CVPR.2018.00326"},{"key":"8640_CR28","doi-asserted-by":"crossref","unstructured":"Qin X, Zhang Z, Huang C, Gao C, Dehghan M, Jagersand M (2019) Basnet: Boundary-aware salient object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7479\u20137489","DOI":"10.1109\/CVPR.2019.00766"},{"key":"8640_CR29","doi-asserted-by":"crossref","unstructured":"Zhao T, Wu X (2019) Pyramid feature attention network for saliency detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3085\u20133094","DOI":"10.1109\/CVPR.2019.00320"},{"key":"8640_CR30","doi-asserted-by":"crossref","unstructured":"Siris A, Jiao J, Tam GK, Xie X, Lau RW (2021) Scene context-aware salient object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4156\u20134166","DOI":"10.1109\/ICCV48922.2021.00412"},{"key":"8640_CR31","doi-asserted-by":"publisher","first-page":"6226","DOI":"10.1109\/TIP.2021.3093380","volume":"30","author":"Z Wu","year":"2021","unstructured":"Wu Z, Su L, Huang Q (2021) Decomposition and completion network for salient object detection. IEEE Trans Image Process 30:6226\u20136239","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"8640_CR32","doi-asserted-by":"publisher","first-page":"095055","DOI":"10.1117\/1.JRS.9.095055","volume":"9","author":"D Zhao","year":"2015","unstructured":"Zhao D, Wang J, Shi J, Jiang Z (2015) Sparsity-guided saliency detection for remote sensing images. J Appl Remote Sens 9(1):095055","journal-title":"J Appl Remote Sens"},{"issue":"22","key":"8640_CR33","doi-asserted-by":"publisher","first-page":"8270","DOI":"10.1080\/01431161.2019.1608384","volume":"40","author":"L Zhang","year":"2019","unstructured":"Zhang L, Liu Y, Zhang J (2019) Saliency detection based on self-adaptive multiple feature fusion for remote sensing images. Int J Remote Sens 40(22):8270\u20138297","journal-title":"Int J Remote Sens"},{"issue":"11","key":"8640_CR34","doi-asserted-by":"publisher","first-page":"9156","DOI":"10.1109\/TGRS.2019.2925070","volume":"57","author":"C Li","year":"2019","unstructured":"Li C, Cong R, Hou J, Zhang S, Qian Y, Kwong S (2019) Nested network with two-stream pyramid for salient object detection in optical remote sensing images. IEEE Trans Geosci Remote Sens 57(11):9156\u20139166","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"8640_CR35","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.neucom.2020.05.108","volume":"415","author":"C Li","year":"2020","unstructured":"Li C, Cong R, Guo C, Li H, Zhang C, Zheng F, Zhao Y (2020) A parallel down-up fusion network for salient object detection in optical remote sensing images. Neurocomputing 415:411\u2013420","journal-title":"Neurocomputing"},{"key":"8640_CR36","doi-asserted-by":"crossref","unstructured":"Zhou X, Shen K, Liu Z, Gong C, Zhang J, Yan C (2021) Edge-aware multiscale feature integration network for salient object detection in optical remote sensing images. IEEE Trans Geosci Remote Sens","DOI":"10.1109\/TGRS.2021.3091312"},{"key":"8640_CR37","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3101359","author":"Z Tu","year":"2021","unstructured":"Tu Z, Wang C, Li C, Fan M, Zhao H, Luo B (2021) ORSI salient object detection via multiscale joint region and boundary model. IEEE Trans Geosci Remote Sens. https:\/\/doi.org\/10.1109\/TGRS.2021.3101359","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"8640_CR38","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3131221","author":"G Li","year":"2021","unstructured":"Li G, Liu Z, Lin W, Ling H (2021) Multi-content complementation network for salient object detection in optical remote sensing images. IEEE Trans Geosci Remote Sens. https:\/\/doi.org\/10.1109\/TGRS.2021.3131221","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"8640_CR39","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3123984","author":"R Cong","year":"2021","unstructured":"Cong R, Zhang Y, Fang L, Li J, Zhang C, Zhao Y, Kwong S (2021) RRNet: relational reasoning network with parallel multi-scale attention for salient object detection in optical remote sensing images. IEEE Trans Geosci Remote Sens. https:\/\/doi.org\/10.1109\/TGRS.2021.3123984","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"8640_CR40","doi-asserted-by":"crossref","unstructured":"Carion N, Massa F, Synnaeve G, Usunier N, Kirillov A, Zagoruyko S (2020) End-to-end object detection with transformers. In: European conference on computer vision, pp 213\u2013229. Springer, Berlin","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"8640_CR41","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, et al (2020) An image is worth 16x16 words: transformers for image recognition at scale. arXiv preprint arXiv:2010.11929"},{"key":"8640_CR42","doi-asserted-by":"crossref","unstructured":"Ye L, Rochan M, Liu Z, Wang Y (2019) Cross-modal self-attention network for referring image segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10502\u201310511","DOI":"10.1109\/CVPR.2019.01075"},{"key":"8640_CR43","doi-asserted-by":"crossref","unstructured":"Ranftl R, Bochkovskiy A, Koltun V (2021) Vision transformers for dense prediction. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 12179\u201312188","DOI":"10.1109\/ICCV48922.2021.01196"},{"key":"8640_CR44","doi-asserted-by":"crossref","unstructured":"Zheng S, Lu J, Zhao H, Zhu X, Luo Z, Wang Y, Fu Y, Feng J, Xiang T, Torr PH et\u00a0al (2021) Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 6881\u20136890","DOI":"10.1109\/CVPR46437.2021.00681"},{"key":"8640_CR45","doi-asserted-by":"crossref","unstructured":"Wang H, Zhu Y, Adam H, Yuille A, Chen L-C (2021) Max-deeplab: end-to-end panoptic segmentation with mask transformers. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5463\u20135474","DOI":"10.1109\/CVPR46437.2021.00542"},{"key":"8640_CR46","doi-asserted-by":"crossref","unstructured":"Chen H, Wang Y, Guo T, Xu C, Deng Y, Liu Z, Ma S, Xu C, Xu C, Gao W (2021) Pre-trained image processing transformer. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12299\u201312310","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"8640_CR47","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Lin S, Guo B (2021) Swin transformer: hierarchical vision transformer using shifted windows. arXiv preprint arXiv:2103.14030","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"8640_CR48","doi-asserted-by":"crossref","unstructured":"Liu N, Zhang N, Wan K, Shao L, Han J (2021) Visual saliency transformer. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 4722\u20134732","DOI":"10.1109\/ICCV48922.2021.00468"},{"key":"8640_CR49","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03917-2","author":"C Xu","year":"2022","unstructured":"Xu C, Liu X, Zhao W (2022) Attention-guided salient object detection using autoencoder regularization. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-022-03917-2","journal-title":"Appl Intell"},{"key":"8640_CR50","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":"11","key":"8640_CR51","doi-asserted-by":"publisher","first-page":"9682","DOI":"10.1109\/TGRS.2020.3045708","volume":"59","author":"L Zhang","year":"2021","unstructured":"Zhang L, Ma J (2021) Salient object detection based on progressively supervised learning for remote sensing images. IEEE Trans Geosci Remote Sens 59(11):9682\u20139696","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"8640_CR52","doi-asserted-by":"crossref","unstructured":"Achanta R, Hemami S, Estrada F, Susstrunk S (2009) Frequency-tuned salient region detection. In: 2009 IEEE conference on computer vision and pattern recognition, pp 1597\u20131604. IEEE","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"8640_CR53","doi-asserted-by":"crossref","unstructured":"Fan D-P, Cheng M-M, Liu Y, Li T, Borji A (2017) Structure-measure: a new way to evaluate foreground maps. In: Proceedings of the IEEE international conference on computer vision, pp 4548\u20134557","DOI":"10.1109\/ICCV.2017.487"},{"key":"8640_CR54","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"8640_CR55","unstructured":"You Y, Gitman I, Ginsburg B (2017) Scaling sgd batch size to 32k for imagenet training. arXiv preprint arXiv:1708.03888"},{"key":"8640_CR56","doi-asserted-by":"crossref","unstructured":"Zhu W, Liang S, Wei Y, Sun J (2014) Saliency optimization from robust background detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2814\u20132821","DOI":"10.1109\/CVPR.2014.360"},{"issue":"3","key":"8640_CR57","doi-asserted-by":"publisher","first-page":"1311","DOI":"10.1109\/TIP.2017.2762422","volume":"27","author":"Y Yuan","year":"2017","unstructured":"Yuan Y, Li C, Kim J, Cai W, Feng DD (2017) Reversion correction and regularized random walk ranking for saliency detection. IEEE Trans Image Process 27(3):1311\u20131322","journal-title":"IEEE Trans Image Process"},{"key":"8640_CR58","doi-asserted-by":"crossref","unstructured":"Yang C, Zhang L, Lu H, Ruan X, Yang M-H (2013) Saliency detection via graph-based manifold ranking. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3166\u20133173","DOI":"10.1109\/CVPR.2013.407"},{"key":"8640_CR59","doi-asserted-by":"crossref","unstructured":"Wei Y, Wen F, Zhu W, Sun J (2012) Geodesic saliency using background priors. In: European conference on computer vision, pp 29\u201342. Springer, Berlin","DOI":"10.1007\/978-3-642-33712-3_3"},{"key":"8640_CR60","doi-asserted-by":"crossref","unstructured":"Perazzi F, Kr\u00e4henb\u00fchl P, Pritch Y, Hornung A (2012) Saliency filters: contrast based filtering for salient region detection. In: 2012 IEEE conference on computer vision and pattern recognition, pp 733\u2013740. IEEE","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"8640_CR61","doi-asserted-by":"crossref","unstructured":"Wu Z, Su L, Huang Q (2019) Stacked cross refinement network for edge-aware salient object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp. 7264\u20137273","DOI":"10.1109\/ICCV.2019.00736"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08640-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08640-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08640-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T17:53:24Z","timestamp":1690394004000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08640-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,20]]},"references-count":61,"journal-issue":{"issue":"24","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["8640"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08640-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,20]]},"assertion":[{"value":"20 October 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 May 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 May 2023","order":3,"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"}}]}}