{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T14:57:07Z","timestamp":1782226627375,"version":"3.54.5"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2018,2,1]],"date-time":"2018-02-01T00:00:00Z","timestamp":1517443200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61473144"],"award-info":[{"award-number":["61473144"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["41661083"],"award-info":[{"award-number":["41661083"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61602222"],"award-info":[{"award-number":["61602222"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61562044"],"award-info":[{"award-number":["61562044"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Aeronautical Science Foundation of Chin","award":["20162852031"],"award-info":[{"award-number":["20162852031"]}]},{"name":"the National Science Foundation of Jiangxi Province","award":["20171BAB212014"],"award-info":[{"award-number":["20171BAB212014"]}]},{"name":"The special scientific instrument development of Ministry of science and technology of China","award":["2016YFF0103702"],"award-info":[{"award-number":["2016YFF0103702"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Wireless Com Network"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1186\/s13638-018-1022-8","type":"journal-article","created":{"date-parts":[[2018,2,1]],"date-time":"2018-02-01T07:33:42Z","timestamp":1517470422000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Aircraft detection in remote sensing images based on saliency and convolution neural network"],"prefix":"10.1186","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7780-5646","authenticated-orcid":false,"given":"Guoxiong","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaming","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Gong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naixue","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,2,1]]},"reference":[{"issue":"6","key":"1022_CR1","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.3390\/s17061303","volume":"17","author":"PF Wu","year":"2017","unstructured":"PF Wu, F Xiao, C Sha, HP Huang, RC Wang, NX Xiong, Node scheduling strategies for achieving full-view area coverage in camera sensor networks. Sensors 17(6), 1303 (2017). https:\/\/doi.org\/10.3390\/s17061303","journal-title":"Sensors"},{"key":"1022_CR2","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.ins.2017.04.035","volume":"408","author":"YH Wang","year":"2017","unstructured":"YH Wang, KL Chen, JN Yu, NX Xiong, H Leung, HL Zhou, L Zhu, Dynamic propagation characteristics estimation and tracking based on an EM-EKF algorithm in time-variant MIMO channel. Inf. Sci. 408, 70\u201383 (2017). https:\/\/doi.org\/10.1016\/j.ins.2017.04.035","journal-title":"Inf. Sci."},{"key":"1022_CR3","doi-asserted-by":"publisher","first-page":"2396","DOI":"10.1109\/ACCESS.2017.2672561","volume":"5","author":"J Gui","year":"2017","unstructured":"J Gui, L Hui, NX Xiong, A game-based localized multi-objective topology control scheme in heterogeneous wireless networks. IEEE Access 5, 2396\u20132416 (2017). https:\/\/doi.org\/10.1109\/ACCESS.2017.2672561","journal-title":"IEEE Access"},{"key":"1022_CR4","doi-asserted-by":"publisher","unstructured":"NX Xiong, RW Liu, MH Liang, D Wu, Z Liu, HS Wu, Effective alternating direction optimization methods for sparsity-constrained blind image deblurring. Sensors 17(1) (2017). https:\/\/doi.org\/10.3390\/s17010174","DOI":"10.3390\/s17010174"},{"issue":"7","key":"1022_CR5","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.6138\/JIT.2016.17.7.20161108","volume":"17","author":"H Zhang","year":"2016","unstructured":"H Zhang, RW Liu, D Wu, YL Liu, NN Xiong, Non-convex total generalized variation with spatially adaptive regularization parameters for edge-preserving image restoration. Journal of Internet Technology 17(7), 1391\u20131403 (2016). https:\/\/doi.org\/10.6138\/JIT.2016.17.7.20161108","journal-title":"Journal of Internet Technology"},{"issue":"4","key":"1022_CR6","doi-asserted-by":"publisher","first-page":"1947","DOI":"10.1007\/s11042-014-2381-8","volume":"75","author":"ZH Xia","year":"2016","unstructured":"ZH Xia, XH Wang, XM Sun, QS Liu, NX Xiong, Steganalysis of LSB matching using differences between nonadjacent pixels. Multimedia Tools & Applications 75(4), 1947\u20131962 (2016). https:\/\/doi.org\/10.1007\/s11042-014-2381-8","journal-title":"Multimedia Tools & Applications"},{"issue":"1","key":"1022_CR7","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/s10586-015-0499-8","volume":"19","author":"LP Gao","year":"2016","unstructured":"LP Gao, FY Yu, QK Chen, NX Xiong, Consistency maintenance of do and undo\/redo operations in real-time collaborative bitmap editing systems. Clust. Comput. 19(1), 255\u2013267 (2016). https:\/\/doi.org\/10.1007\/s10586-015-0499-8","journal-title":"Clust. Comput."},{"key":"1022_CR8","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.ins.2016.12.030","volume":"387","author":"ZH Xia","year":"2017","unstructured":"ZH Xia, NN Xiong, AV Vasilakos, XM Sun, EPCBIR, An efficient and privacy-preserving content-based image retrieval scheme in cloud computing. Inf. Sci. 387, 195\u2013204 (2017). https:\/\/doi.org\/10.1016\/j.ins.2016.12.030","journal-title":"Inf. Sci."},{"key":"1022_CR9","doi-asserted-by":"publisher","unstructured":"Z Lu, YR Lin, XX Huang, NX Xiong, ZJ Fang, Visual topic discovering, tracking and summarization from social media streams. Multimedia Tools & Applications. 1\u201325(2017). DOI: https:\/\/doi.org\/10.1007\/s11042-016-3877-1","DOI":"10.1007\/s11042-016-3877-1"},{"issue":"5","key":"1022_CR10","doi-asserted-by":"publisher","first-page":"297","DOI":"10.14257\/ijsip.2016.9.5.27","volume":"9","author":"L Shu","year":"2016","unstructured":"L Shu, YM Fang, ZJ Fang, Y Yang, FC Fei, NX Xiong, A novel objective quality assessment for super- resolution images. International Journal of Signal Processing, Image Processing and Pattern Recognition 9(5), 297\u2013308 (2016). https:\/\/doi.org\/10.14257\/ijsip.2016.9.5.27","journal-title":"International Journal of Signal Processing, Image Processing and Pattern Recognition"},{"key":"1022_CR11","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.ins.2014.06.022","volume":"283","author":"WW Fang","year":"2014","unstructured":"WW Fang, YC Li, HJ Zhang, NX Xiong, JY Lai, AV Vasilakos, On the throughput-energy tradeoff for data transmission between cloud and mobile devices. Inf. Sci. 283, 79\u201393 (2014). https:\/\/doi.org\/10.1016\/j.ins.2014.06.022","journal-title":"Inf. Sci."},{"issue":"4","key":"1022_CR12","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1109\/JSAC.2009.090512","volume":"27","author":"NX Xiong","year":"2009","unstructured":"NX Xiong, AV Vasilakos, LT Yang, LY Song, Y Pan, R Kannan, YS Li, Y Li, Comparative analysis of quality of service and memory usage for adaptive failure detectors in healthcare systems. IEEE Journal on Selected Areas in Communications 27(4), 495\u2013509 (2009). https:\/\/doi.org\/10.1109\/JSAC.2009.090512","journal-title":"IEEE Journal on Selected Areas in Communications"},{"issue":"8","key":"1022_CR13","doi-asserted-by":"publisher","first-page":"3562","DOI":"10.1007\/s11227-016-1821-9","volume":"73","author":"X Lu","year":"2017","unstructured":"X Lu, LL Tu, XY Zhou, NX Xiong, LM Sun, ViMediaNet: an emulation system for interactive multimedia based telepresence services. J. Supercomput. 73(8), 3562\u20133578 (2017). https:\/\/doi.org\/10.1007\/s11227-016-1821-9","journal-title":"J. Supercomput."},{"issue":"7","key":"1022_CR14","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.6138\/JIT.2015.16.7.20151103a","volume":"16","author":"CY Zhang","year":"2015","unstructured":"CY Zhang, D Wu, RW Liu, NX Xiong, Non-local regularized variational model for image deblurring under mixed Gaussian-impulse noise. Journal of Internet Technology 16(7), 1301\u20131319 (2015). https:\/\/doi.org\/10.6138\/JIT.2015.16.7.20151103a","journal-title":"Journal of Internet Technology"},{"issue":"11","key":"1022_CR15","doi-asserted-by":"publisher","first-page":"2249","DOI":"10.1016\/j.ins.2009.12.001","volume":"180","author":"NX Xiong","year":"2010","unstructured":"NX Xiong, AV Vasilakos, LT Yang, CX Wang, R Kannan, CC Chang, Y Pan, A novel self-tuning feedback controller for active queue management supporting TCP flows. Inf. Sci. 180(11), 2249\u20132263 (2010). https:\/\/doi.org\/10.1016\/j.ins.2009.12.001","journal-title":"Inf. Sci."},{"issue":"12","key":"1022_CR16","doi-asserted-by":"publisher","first-page":"22408","DOI":"10.3390\/s141222408","volume":"14","author":"Y Yang","year":"2014","unstructured":"Y Yang, S Tong, S Huang, P Lin, Dual-tree complex wavelet transform and image block residual-based multi-focus image fusion in visual sensor networks. Sensors 14(12), 22408\u201322430 (2014). https:\/\/doi.org\/10.3390\/s141222408","journal-title":"Sensors"},{"issue":"11","key":"1022_CR17","doi-asserted-by":"publisher","first-page":"2956","DOI":"10.1109\/TSMC.2016.2557225","volume":"47","author":"YM Fang","year":"2017","unstructured":"YM Fang, ZJ Fang, FN Yuan, Y Yang, SY Yang, NN Xiong, Optimized multioperator image retargeting based on perceptual similarity measure. IEEE Transactions on Systems Man Cybernetics-Systems 47(11), 2956\u20132966 (2017). https:\/\/doi.org\/10.1109\/TSMC.2016.2557225","journal-title":"IEEE Transactions on Systems Man Cybernetics-Systems"},{"issue":"5","key":"1022_CR18","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1109\/LGRS.2017.2672560","volume":"14","author":"T Li","year":"2017","unstructured":"T Li, JP Zhang, XC Lu, Y Zhang, SDBD: A hierarchical region-of-interest detection approach in large-scale remote sensing image. IEEE Geoscience & Remote Sensing Letters. 14(5), 699\u2013703 (2017). https:\/\/doi.org\/10.1109\/LGRS.2017.2672560","journal-title":"IEEE Geoscience & Remote Sensing Letters."},{"key":"1022_CR19","doi-asserted-by":"publisher","unstructured":"QH Luo, ZW Shi, in Proc. of 2016 IEEE International Geoscience and Remote Sensing Symposium(IGARSS). Airplane detection in remote sensing images based on Object Proposal(IEEE, Beijing, 2016), pp. 1388\u20131391. DOI: https:\/\/doi.org\/10.1109\/IGARSS.2016.7729355","DOI":"10.1109\/IGARSS.2016.7729355"},{"issue":"8","key":"1022_CR20","doi-asserted-by":"publisher","first-page":"1413","DOI":"10.1109\/LGRS.2017.2715858","volume":"14","author":"A Zhao","year":"2017","unstructured":"A Zhao, K Fu, SY Wang, JW Zuo, YH Zhang, YF Hu, HQ Wang, Aircraft recognition based on landmark detection in remote sensing images. IEEE Geosci. Remote Sens. Lett. 14(8), 1413\u20131417 (2017). https:\/\/doi.org\/10.1109\/LGRS.2017.2715858","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"12","key":"1022_CR21","doi-asserted-by":"publisher","first-page":"14461","DOI":"10.1007\/s11042-016-3857-5","volume":"76","author":"YD Lin","year":"2017","unstructured":"YD Lin, HJ He, HM Tai, F Chen, ZK Yin, Rotation and scale invariant target detection in optical remote sensing images based on pose-consistency voting. Multimedia Tools and Applications 76(12), 14461\u201314483 (2017). https:\/\/doi.org\/10.1007\/s11042-016-3857-5","journal-title":"Multimedia Tools and Applications"},{"issue":"27","key":"1022_CR22","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1016\/j.neucom.2012.12.064","volume":"128","author":"JR Hai","year":"2014","unstructured":"JR Hai, XJ Ya, SZ Guang, Aircraft recognition using modular extreme learning machine. Neurocomputing 128(27), 166\u2013174 (2014). https:\/\/doi.org\/10.1016\/j.neucom.2012.12.064","journal-title":"Neurocomputing"},{"key":"1022_CR23","doi-asserted-by":"publisher","unstructured":"RH Yang, Q Pan, YM Cheng, in proc. of 2006 IEEE International Conference on Machine Learning and Cybernetics. The Application of Wavelet Invariant Moments to Image Recognition(IEEE), Dalian, China, 2006), pp. 3243-3247. DOI: https:\/\/doi.org\/10.1109\/ICMLC.2006.258434","DOI":"10.1109\/ICMLC.2006.258434"},{"issue":"5","key":"1022_CR24","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/0031-3203(87)90080-X","volume":"20","author":"CS Lin","year":"1987","unstructured":"CS Lin, CL Hwang, New forms of shape invariants from elliptic fourier descriptors. Pattern Recogn. 20(5), 535\u2013545 (1987). https:\/\/doi.org\/10.1016\/0031-3203(87)90080-X","journal-title":"Pattern Recogn."},{"issue":"3","key":"1022_CR25","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1109\/TC.1972.5008949","volume":"C-21","author":"CT Zahn","year":"1972","unstructured":"CT Zahn, RZ Roskies, Fourier descriptors for plane closed curves. IEEE Trans. Comput. C-21(3), 269\u2013281 (1972). https:\/\/doi.org\/10.1109\/TC.1972.5008949","journal-title":"IEEE Trans. Comput."},{"key":"1022_CR26","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.isprsjprs.2016.03.014","volume":"117","author":"G Cheng","year":"2016","unstructured":"G Cheng, JW Han, A survey on object detection in optical remote sensing images. ISPRS J. Photogramm. Remote Sens. 117, 11\u201328 (2016). https:\/\/doi.org\/10.1016\/j.isprsjprs.2016.03.014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"3","key":"1022_CR27","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1109\/LGRS.2012.2214022","volume":"10","author":"G Liu","year":"2013","unstructured":"G Liu, X Sun, K Fu, HQ Wang, Aircraft recognition in high-resolution satellite images using coarse-to-fine shape prior. IEEE Geoscience Remote Sensing Letters 10(3), 573\u2013577 (2013). https:\/\/doi.org\/10.1109\/LGRS.2012.2214022","journal-title":"IEEE Geoscience Remote Sensing Letters"},{"issue":"1","key":"1022_CR28","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/LGRS.2014.2328358","volume":"12","author":"QC Wu","year":"2015","unstructured":"QC Wu, H Sun, X Sun, DB Zhang, K Fu, HQ Wang, Aircraft recognition in high-resolution optical satellite remote sensing images. IEEE Geoscience Remote Sensing Letters 12(1), 112\u2013116 (2015). https:\/\/doi.org\/10.1109\/LGRS.2014.2328358","journal-title":"IEEE Geoscience Remote Sensing Letters"},{"issue":"5","key":"1022_CR29","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1109\/LGRS.2012.2183337","volume":"9","author":"Y Li","year":"2012","unstructured":"Y Li, X Sun, HQ Wang, H Sun, XJ Li, Automatic target detection in high-resolution remote sensing images using a contour-based spatial model. IEEE Geoscience Remote Sensing Letters 9(5), 886\u2013890 (2012). https:\/\/doi.org\/10.1109\/LGRS.2012.2183337","journal-title":"IEEE Geoscience Remote Sensing Letters"},{"issue":"6","key":"1022_CR30","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"A Krizhevsky, I Sutskever, GE Hinton, ImageNet classification with deep convolutional neural networks. Commun. ACM 60(6), 84\u201390 (2017). https:\/\/doi.org\/10.1145\/3065386","journal-title":"Commun. ACM"},{"key":"1022_CR31","doi-asserted-by":"publisher","unstructured":"R Girshick, J Donahue, T Darrell, J Malik, in Proc. of 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Rich feature hierarchies for accurate object detection and semantic segmentation(IEEE, Columbus, 2014), pp. 580\u2013587. DOI: https:\/\/doi.org\/10.1109\/CVPR.2014.81","DOI":"10.1109\/CVPR.2014.81"},{"issue":"2","key":"1022_CR32","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/s11263-013-0620-5","volume":"104","author":"JRR Uijlings","year":"2013","unstructured":"JRR Uijlings, KEA van de Sande, T Gevers, AWM Smeulders, Selective search for object recognition. Int. J. Comput. Vis. 104(2), 154\u2013171 (2013). https:\/\/doi.org\/10.1007\/s11263-013-0620-5","journal-title":"Int. J. Comput. Vis."},{"issue":"11","key":"1022_CR33","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"L Itti, C Koch, E Niebur, A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254\u20131259 (1998). https:\/\/doi.org\/10.1109\/34.730558","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1022_CR34","doi-asserted-by":"publisher","unstructured":"R Girshick, in Proc. of 2015 IEEE International Conference on Computer Vision(ICCV). Fast R-CNN(IEEE, Chile, 2015), pp. 1440\u20131448. DOI: https:\/\/doi.org\/10.1109\/ICCV.2015.169","DOI":"10.1109\/ICCV.2015.169"},{"key":"1022_CR35","doi-asserted-by":"publisher","unstructured":"WJ Zhu, S Liang, YC Wei, J Sun, in Proc. of 2014 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Saliency optimization from robust background detection(IEEE, Boston, 2014), pp. 2814\u20132821. DOI: https:\/\/doi.org\/10.1109\/CVPR.2014.360","DOI":"10.1109\/CVPR.2014.360"},{"issue":"3","key":"1022_CR36","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1109\/TPAMI.2014.2345401","volume":"37","author":"MM Cheng","year":"2015","unstructured":"MM Cheng, NJ Mitra, XL Huang, PHS Torr, SM Hu, Global contrast based salient region detection. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 569\u2013582 (2015). https:\/\/doi.org\/10.1109\/TPAMI.2014.2345401","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1022_CR37","doi-asserted-by":"publisher","unstructured":"R Achanta, S Hemami, F Estrada, S Susstrunk, in Proc. of 2009 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Frequency-tuned salient region detection(IEEE, Miami, 2009), pp. 1597\u20131604. DOI: https:\/\/doi.org\/10.1109\/CVPR.2009.5206596","DOI":"10.1109\/CVPR.2009.5206596"},{"issue":"10","key":"1022_CR38","doi-asserted-by":"publisher","first-page":"1915","DOI":"10.1109\/TPAMI.2011.272","volume":"34","author":"S Goferman","year":"2012","unstructured":"S Goferman, L Zelnikmanor, A Tal, Context-aware saliency detection. IEEE Trans. Pattern Anal. Mach. Intell. 34(10), 1915\u20131926 (2012). https:\/\/doi.org\/10.1109\/TPAMI.2011.272","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1022_CR39","doi-asserted-by":"publisher","unstructured":"Y Zhai, M Shah, in Proc. of 2006 ACM International Conference on Multimedia. Visual attention detection in video sequences using spatiotemporal cues(ACM, Santa Barbara, 2006), pp. 815\u2013824. DOI: https:\/\/doi.org\/10.1145\/1180639.1180824","DOI":"10.1145\/1180639.1180824"},{"key":"1022_CR40","doi-asserted-by":"publisher","unstructured":"X Hou, L Zhang, in Proc. of 2007 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Saliency detection: a spectral residual approach(IEEE, Minneapolis, 2007), pp. 1\u20138. DOI: https:\/\/doi.org\/10.1109\/CVPR.2007.383267","DOI":"10.1109\/CVPR.2007.383267"},{"key":"1022_CR41","doi-asserted-by":"publisher","unstructured":"XH Li, HC Lu, LH Zhang, X Ruan, MH Yang, in Proc. of 2013 IEEE International Conference on Computer Vision(ICCV). Saliency detection via dense and sparse reconstruction(IEEE, Sydney, 2013), pp. 2976\u20132983. DOI: https:\/\/doi.org\/10.1109\/ICCV.2013.370","DOI":"10.1109\/ICCV.2013.370"},{"key":"1022_CR42","doi-asserted-by":"publisher","unstructured":"N Tong, HC Lu, R Xiang, MH Yang, in Proc. of 2015 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Salient object detection via bootstrap learning(IEEE, Boston, 2015), pp. 1884\u20131892. DOI: https:\/\/doi.org\/10.1109\/CVPR.2015.7298798","DOI":"10.1109\/CVPR.2015.7298798"},{"issue":"4","key":"1022_CR43","first-page":"219","volume":"4","author":"C Koch","year":"1985","unstructured":"C Koch, S Ullman, Shifts in selective visual attention: towards the underlying neural circuitry. Hum. Neurobiol. 4(4), 219\u2013227 (1985)","journal-title":"Hum. Neurobiol."},{"key":"1022_CR44","doi-asserted-by":"crossref","unstructured":"B Sch\u00f6lkopf, J Platt, T Hofmann. Graph-based visual saliency. in Proceedings of advances in Neural Information Processing Systems (NIPS). (MIT Press, Vancouver, 2006) p.545\u2013552.","DOI":"10.7551\/mitpress\/7503.001.0001"},{"issue":"2","key":"1022_CR45","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1109\/TPAMI.2010.70","volume":"33","author":"T Liu","year":"2011","unstructured":"T Liu, ZJ Yuan, JA Sun, JD Wang, NN Zheng, XO Tang, HY Shum, Learning to detect a salient object. IEEE Trans. Pattern Anal. Mach. Intell. 33(2), 353\u2013367 (2011). https:\/\/doi.org\/10.1109\/TPAMI.2010.70","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"10","key":"1022_CR46","doi-asserted-by":"publisher","first-page":"1915","DOI":"10.1109\/TPAMI.2011.272","volume":"34","author":"S Goferman","year":"2012","unstructured":"S Goferman, L Zelnik-Manor, A Tal, Context-aware saliency detection. IEEE Trans. Pattern Anal. Mach. Intell. 34(10), 1915\u20131926 (2012). https:\/\/doi.org\/10.1109\/TPAMI.2011.272","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1022_CR47","doi-asserted-by":"publisher","unstructured":"A Borji, L Itti, in Proc. of 2012 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Exploiting local and global patch rarities for saliency detection(IEEE, Providence, 2012), pp. 478\u2013485. DOI: https:\/\/doi.org\/10.1109\/CVPR.2012.6247711","DOI":"10.1109\/CVPR.2012.6247711"},{"key":"1022_CR48","doi-asserted-by":"publisher","unstructured":"J Feng, YC Wei, LT Tao, C Zhang, J Sun, in Proc. of 2011 IEEE International Conference on Computer Vision(ICCV). Salient object detection by composition(IEEE, Barcelona, 2011), pp. 1028\u20131035. DOI: https:\/\/doi.org\/10.1109\/ICCV.2011.6126348","DOI":"10.1109\/ICCV.2011.6126348"},{"key":"1022_CR49","doi-asserted-by":"publisher","unstructured":"M Ran, A Tal, L Zelnik-Manor, in Proc. of 2013 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). What makes a patch distinct?(IEEE, Portland, 2013), pp. 1139\u20131146. DOI: https:\/\/doi.org\/10.1109\/CVPR.2013.151","DOI":"10.1109\/CVPR.2013.151"},{"key":"1022_CR50","doi-asserted-by":"publisher","unstructured":"F Perazzi, P Krahenbuhl, Y Pritch, A Hornung, in Proc. of 2012 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Saliency filters: contrast based filtering for salient region detection(IEEE, Providence, 2012), pp. 733\u2013740. DOI: https:\/\/doi.org\/10.1109\/CVPR.2012.6247743","DOI":"10.1109\/CVPR.2012.6247743"},{"issue":"1","key":"1022_CR51","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1109\/TIP.2009.2030969","volume":"19","author":"CL Guo","year":"2010","unstructured":"CL Guo, LM Zhang, A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Trans. Image Process. 19(1), 185\u2013198 (2010). https:\/\/doi.org\/10.1109\/TIP.2009.2030969","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"1022_CR52","doi-asserted-by":"publisher","first-page":"5012","DOI":"10.1109\/TIP.2016.2602079","volume":"25","author":"G Li","year":"2016","unstructured":"G Li, Y Yu, Visual saliency detection based on multiscale deep CNN features. IEEE Trans. Image Process. 25(11), 5012\u20135024 (2016). https:\/\/doi.org\/10.1109\/TIP.2016.2602079","journal-title":"IEEE Trans. Image Process."},{"key":"1022_CR53","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.neucom.2016.10.073","volume":"257","author":"P Zhang","year":"2017","unstructured":"P Zhang, T Zhuo, W Huang, K Chen, M Kankanhalli, Online object tracking based on CNN with spatial-temporal saliency guided sampling. Neurocomputing 257, 115\u2013127 (2017). https:\/\/doi.org\/10.1016\/j.neucom.2016.10.073","journal-title":"Neurocomputing"},{"issue":"2","key":"1022_CR54","first-page":"243","volume":"5","author":"JS Lim","year":"2012","unstructured":"JS Lim, WH Kim, Detection of multiple humans using motion information and adaboost algorithm based on harr-like features. International Journal of Hybrid Information Technology 5(2), 243\u2013248 (2012)","journal-title":"International Journal of Hybrid Information Technology"},{"issue":"19","key":"1022_CR55","doi-asserted-by":"publisher","first-page":"10","DOI":"10.5120\/20084-2026","volume":"114","author":"PY Reecha","year":"2015","unstructured":"PY Reecha, V Senthamilarasu, K Kutty, PU Sunita, Implementation of robust HOG-SVM based pedestrian classification. International Journal of Computer Applications 114(19), 10\u201316 (2015). https:\/\/doi.org\/10.5120\/20084-2026","journal-title":"International Journal of Computer Applications"},{"issue":"1","key":"1022_CR56","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s11265-015-1097-y","volume":"86","author":"L Hou","year":"2017","unstructured":"L Hou, WG Wan, KH Lee, JN Hwang, G Okopal, J Pitton, Robust human tracking based on DPM constrained multiple-kernel from a moving camera. Journal of Signal Processing Systems. 86(1), 27\u201339 (2017). https:\/\/doi.org\/10.1007\/s11265-015-1097-y","journal-title":"Journal of Signal Processing Systems."},{"key":"1022_CR57","doi-asserted-by":"publisher","unstructured":"A Ali, MA Bayoumi, in Proc. of 2016 IEEE International Conference on Image Processing. Towards real-time DPM object detector for driver assistance(IEEE, Arizona, 2016), pp. 3842\u20133846. DOI: https:\/\/doi.org\/10.1109\/ICIP.2016.7533079","DOI":"10.1109\/ICIP.2016.7533079"},{"key":"1022_CR58","doi-asserted-by":"publisher","unstructured":"S Bell, CL Zitnick, K Bala, R Girshick, in Proc. of 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Inside-outside net: detecting objects in context with skip pooling and recurrent neural networks(IEEE, Las Vegas, 2016), pp. 2874\u20132883. DOI: https:\/\/doi.org\/10.1109\/CVPR.2016.314","DOI":"10.1109\/CVPR.2016.314"},{"key":"1022_CR59","doi-asserted-by":"publisher","unstructured":"T Kong, A Yao, Y Chen, FC Sun, in Proc. of 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). HyperNet: towards accurate region proposal generation and joint object detection(IEEE, Las Vegas, 2016), pp. 845\u2013853. DOI: https:\/\/doi.org\/10.1109\/CVPR.2016.98","DOI":"10.1109\/CVPR.2016.98"},{"key":"1022_CR60","doi-asserted-by":"publisher","unstructured":"F Yang, W Choi, Y Lin, in Proc. of 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Exploit all the layers: fast and accurate CNN object detector with scale dependent pooling and cascaded rejection classifiers(IEEE, Las Vegas, 2016), pp. 2129\u20132137. DOI: https:\/\/doi.org\/10.1109\/CVPR.2016.234","DOI":"10.1109\/CVPR.2016.234"},{"issue":"9","key":"1022_CR61","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"KM He","year":"2015","unstructured":"KM He, XY Zhang, SQ Ren, J Sun, Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1904\u20131916 (2015). https:\/\/doi.org\/10.1109\/TPAMI.2015.2389824","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"1022_CR62","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"SQ Ren","year":"2017","unstructured":"SQ Ren, KM He, R Girshick, J Sun, Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis & Machine Intelligence 39(6), 1137\u20131149 (2017). https:\/\/doi.org\/10.1109\/TPAMI.2016.2577031","journal-title":"IEEE Transactions on Pattern Analysis & Machine Intelligence"},{"key":"1022_CR63","unstructured":"JF Dai, Y Li, KM He, J Sun, R-FCN: object detection via region-based fully convolutional networks(2016), https:\/\/arxiv.org\/abs\/1605.06409 , Accessed 21 Jun 2016."},{"key":"1022_CR64","doi-asserted-by":"publisher","unstructured":"J Redmon, S Divvala, R Girshick, A Farhadi, in Proc. of 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). You only look once: unified, real-time object detection(IEEE, Las Vegas, 2016), pp. 779\u2013788. doi: https:\/\/doi.org\/10.1109\/CVPR.2016.91","DOI":"10.1109\/CVPR.2016.91"},{"key":"1022_CR65","doi-asserted-by":"publisher","unstructured":"W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg, in Proc. of 2016 the 14th European Conference on Computer Vision(ECCV). SSD: Single Shot MultiBox Detector(Springer, Amsterdam, 2016), pp. 21\u201337. DOI: https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"1022_CR66","doi-asserted-by":"publisher","unstructured":"CL Zitnick, P Doll\u00e1r, in Proc. of 2014 the 13th European Conference on Computer Vision(ECCV). Edge boxes: locating object proposals from edges(Springer, Zurich, 2014), pp. 391\u2013405. DOI: https:\/\/doi.org\/10.1007\/978-3-319-10602-1_26","DOI":"10.1007\/978-3-319-10602-1_26"},{"key":"1022_CR67","doi-asserted-by":"publisher","unstructured":"M Najibi, M Rastegari, LS Davis, in Proc. of 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). G-CNN: an iterative grid based object detector(IEEE, Las Vegas, 2016), pp. 2369\u20132377. DOI: https:\/\/doi.org\/10.1109\/CVPR.2016.260","DOI":"10.1109\/CVPR.2016.260"},{"key":"1022_CR68","doi-asserted-by":"publisher","unstructured":"J Huang, V Rathod, C Sun, ML Zhu, A Korattikara, A Fathi, I Fischer, Z Wojna, Y Song, S Guadarrama, K Murphy, in Proc. of 2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Speed\/accuracy trade-offs for modern convolutional object detectors (IEEE, Honolulu, 2017), pp. 3296\u20133297. DOI: https:\/\/doi.org\/10.1109\/CVPR.2017.351","DOI":"10.1109\/CVPR.2017.351"},{"key":"1022_CR69","doi-asserted-by":"publisher","unstructured":"Z. Cai, Q. Fan, RS. Feris, N Vasconcelos, in Proc. of 2016 the 14th European Conference on Computer Vision(ECCV). A unified multi-scale deep convolutional neural network for fast object detection(Springer, Amsterdam, 2016), pp. 354\u2013370. DOI: https:\/\/doi.org\/10.1007\/978-3-319-46493-0_22","DOI":"10.1007\/978-3-319-46493-0_22"},{"key":"1022_CR70","doi-asserted-by":"publisher","unstructured":"TY. Lin, P. Doll\u00e1r, R. Girshick, KM He, B Hariharan, S Belongie, in Proc. of 2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Feature pyramid networks for object detection(IEEE, Honolulu, 2017), pp. 936\u2013944. DOI: https:\/\/doi.org\/10.1109\/CVPR.2017.106","DOI":"10.1109\/CVPR.2017.106"},{"key":"1022_CR71","unstructured":"A Shrivastava, R Sukthankar, J Malik, A Gupta, Beyond skip connections: top-down modulation for object detection (2017), https:\/\/arxiv.org\/abs\/1612.06851 , Accessed 19 Sep 2017."},{"key":"1022_CR72","doi-asserted-by":"publisher","unstructured":"J Ren, XH Chen, JB Liu, WX Sun, JH Pang, Q Yan, YW Tai, L Xu, in Proc. of 2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Accurate single stage detector using recurrent rolling convolution(IEEE, Honolulu, 2017), pp. 752\u2013760. DOI: https:\/\/doi.org\/10.1109\/CVPR.2017.87","DOI":"10.1109\/CVPR.2017.87"},{"key":"1022_CR73","unstructured":"CY Fu, W Liu, A Ranga, A Tyagi, AC Berg, DSSD : deconvolutional single shot detector (2017), https:\/\/arxiv.org\/abs\/1701.06659 , Accessed 23 Jan 2017."},{"key":"1022_CR74","unstructured":"KM He, G Gkioxari, P Doll\u00e1r, R Girshick, Mask R-CNN(2017), https:\/\/arxiv.org\/abs\/1703.06870 , Accessed 5 Apr 2017."},{"issue":"11","key":"1022_CR75","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"R Achanta, A Shaji, K Smith, A Lucchi, P Fua, S Susstrunk, SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274\u20132281 (2012). https:\/\/doi.org\/10.1109\/TPAMI.2012.120","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["EURASIP Journal on Wireless Communications and Networking"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s13638-018-1022-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13638-018-1022-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13638-018-1022-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T23:56:07Z","timestamp":1570665367000},"score":1,"resource":{"primary":{"URL":"https:\/\/jwcn-eurasipjournals.springeropen.com\/articles\/10.1186\/s13638-018-1022-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,1]]},"references-count":75,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["1022"],"URL":"https:\/\/doi.org\/10.1186\/s13638-018-1022-8","relation":{},"ISSN":["1687-1499"],"issn-type":[{"value":"1687-1499","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,1]]},"assertion":[{"value":"15 October 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 February 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Guoxiong Hu is currently a doctoral student at College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, China. He works at Jiangxi Normal University, China. Currently, he majors research fields including pattern recognition, image processing, and deep learning.Zhong Yang, he is a professor and doctoral supervisor at College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, China. He has published about more than 100 research papers (including about 30 SCI\/EI-indexed papers). He currently majors research fields including robot control and pattern recognition.Jiaming Han is currently a doctoral student at College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, China. He currently majors research fields including pattern recognition, image processing, and deep learning. Li Huang is currently a doctoral student at School of Information Technology, Jiangxi University of Finance and Economics, China. She works at Jiangxi Normal University, China. She currently majors research fields including information management and knowledge management. Jun Gong is a teacher in the College of Software, Jiangxi Normal University, Nanchang, China. And he earned the PhD degrees from Wuhan University, Wuhan, China in 2016.Neal N. Xiong is currently an Associate Professor (the third year) at Department of Mathematics and Computer Science, Northeastern State University, OK, USA. He received both his PhD degrees in Wuhan University (about sensor system engineering) and the Japan Advanced Institute of Science and Technology (about dependable sensor networks). Before he attended Northeastern State University, he worked at Georgia State University, Wentworth Technology Institution, and Colorado Technical University about 10\u00a0years. His research interests include Cloud Computing, Security and Dependability, Parallel and Distributed Computing, Networks, and Optimization Theory.Dr. Xiong published over 280 international journal papers and over 120 international conference papers. Some of his works were published in IEEE JSAC, IEEE or ACM transactions, ACM Sigcomm workshop, IEEE INFOCOM, ICDCS, and IPDPS. He has been a General Chair, Program Chair, Publicity Chair, PC member and OC member of over 100 international conferences, and as a reviewer of about 100 international journals, including IEEE JSAC, IEEE SMC (Park: A\/B\/C), IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, IEEE Trans. on Parallel and Distributed Systems. He is serving as an Editor-in-Chief, Associate editor, or Editor member for over 10 international journals (including Associate Editor for IEEE Tran. on Systems, Man, and Cybernetics: Systems, Associate Editor for Information Science, Editor-in-Chief of Journal of Internet Technology (JIT), and Editor-in-Chief of Journal of Parallel and Cloud Computing (PCC)), and a guest editor for over 10 international journals, including Sensor Journal, WINET, and MONET. He has received the Best Paper Award at the 10th IEEE International Conference on High Performance Computing and Communications (HPCC-08) and the Best student Paper Award at the 28th North American Fuzzy Information Processing Society Annual Conference (NAFIPS2009).Dr. Xiong is the Chair of \u201cTrusted Cloud Computing\u201d Task Force, IEEE Computational Intelligence Society (CIS), and the Industry System Applications Technical Committee; he is a Senior member of IEEE Computer Society, E-mail: xiongnaixue@gmail.com.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Authors\u2019 information"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Publisher\u2019s Note"}}],"article-number":"26"}}