{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T23:44:22Z","timestamp":1775259862306,"version":"3.50.1"},"reference-count":76,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2018,10,30]],"date-time":"2018-10-30T00:00:00Z","timestamp":1540857600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Vision and Applications"],"published-print":{"date-parts":[[2019,2]]},"DOI":"10.1007\/s00138-018-0988-x","type":"journal-article","created":{"date-parts":[[2018,10,30]],"date-time":"2018-10-30T07:24:20Z","timestamp":1540884260000},"page":"163-176","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Weighted-learning-instance-based retrieval model using instance distance"],"prefix":"10.1007","volume":"30","author":[{"given":"Hao","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueli","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohan","family":"Bi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linna","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongfang","family":"Bie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junqi","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,10,30]]},"reference":[{"issue":"1","key":"988_CR1","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1006\/jvci.1999.0413","volume":"10","author":"Y Rui","year":"1999","unstructured":"Rui, Y., Huang, T.S., Chang, S.F.: Image retrieval: current techniques, promising directions, and open issues. J. Vis. Commun. Image Represent. 10(1), 39\u201362 (1999)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"988_CR2","doi-asserted-by":"crossref","unstructured":"Eakins, J., Graham, M.: Content-based image retrieval (1999)","DOI":"10.1049\/ic:19990883"},{"key":"988_CR3","doi-asserted-by":"publisher","first-page":"111","DOI":"10.2307\/271063","volume":"25","author":"AE Raftery","year":"1995","unstructured":"Raftery, A.E.: Bayesian model selection in social research. Sociol. Methodol. 25, 111\u2013163 (1995)","journal-title":"Sociol. Methodol."},{"key":"988_CR4","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1109\/TC.1981.1675772","volume":"4","author":"E Horowitz","year":"1981","unstructured":"Horowitz, E., Zorat, A.: The binary tree as an interconnection network: applications to multiprocessor systems and VLSI. IEEE Trans. Comput. 4, 247\u2013253 (1981)","journal-title":"IEEE Trans. Comput."},{"issue":"8","key":"988_CR5","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","volume":"31","author":"AK Jain","year":"2010","unstructured":"Jain, A.K.: Data clustering: 50\u00a0years beyond K-means[J]. Pattern Recogn. Lett. 31(8), 651\u2013666 (2010)","journal-title":"Pattern Recogn. Lett."},{"issue":"3","key":"988_CR6","first-page":"27","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 27 (2011)","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"},{"key":"988_CR7","doi-asserted-by":"crossref","unstructured":"Lin, Y., Lv, F., Zhu, S., et al.: Large-scale image classification: fast feature extraction and SVM training. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1689\u20131696. IEEE, Washington (2011)","DOI":"10.1109\/CVPR.2011.5995477"},{"key":"988_CR8","doi-asserted-by":"crossref","unstructured":"Wang, J., Yang, J., Yu, K., et al.: Locality-constrained linear coding for image classification. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3360\u20133367. IEEE, Washington (2010)","DOI":"10.1109\/CVPR.2010.5540018"},{"issue":"7","key":"988_CR9","doi-asserted-by":"publisher","first-page":"2801","DOI":"10.1016\/j.camwa.2011.07.046","volume":"62","author":"NK Alham","year":"2011","unstructured":"Alham, N.K., Li, M., Liu, Y., et al.: A MapReduce-based distributed SVM algorithm for automatic image annotation. Comput. Math Appl. 62(7), 2801\u20132811 (2011)","journal-title":"Comput. Math Appl."},{"key":"988_CR10","doi-asserted-by":"crossref","unstructured":"Malisiewicz, T., Gupta, A., Efros, A.A.: Ensemble of exemplar-SVMs for object detection and beyond. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 89\u201396. IEEE, Washington (2011)","DOI":"10.1109\/ICCV.2011.6126229"},{"key":"988_CR11","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","volume":"187","author":"Y Guo","year":"2016","unstructured":"Guo, Y., Liu, Y., Oerlemans, A., et al.: Deep learning for visual understanding: a review. Neurocomputing 187, 27\u201348 (2016)","journal-title":"Neurocomputing"},{"key":"988_CR12","doi-asserted-by":"crossref","unstructured":"Cheng, G., Zhou, P., Han, J.: RIFD-CNN: rotation-invariant and fisher discriminative convolutional neural networks for object detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2884\u20132893. IEEE Computer Society, Washington (2016)","DOI":"10.1109\/CVPR.2016.315"},{"key":"988_CR13","doi-asserted-by":"crossref","unstructured":"Fu, J., Zheng, H., Mei, T.: Look closer to see better: recurrent attention convolutional neural network for fine-grained image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 4476\u20134484. IEEE Computer Society, Washington (2017)","DOI":"10.1109\/CVPR.2017.476"},{"issue":"9","key":"988_CR14","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"K He","year":"2015","unstructured":"He, K., Zhang, X., Ren, S., et al.: Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1904\u20131916 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"7","key":"988_CR15","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"key":"988_CR16","unstructured":"Salakhutdinov, R., Hinton, G.E.: Deep Boltzmann machines. In: AISTATS, vol. 1, p. 3 (2009)"},{"key":"988_CR17","unstructured":"Ngiam, J., Chen, Z., Koh, P.W., et al.: Learning deep energy models. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp. 1105\u20131112 (2011)"},{"key":"988_CR18","doi-asserted-by":"crossref","unstructured":"Poultney, C., Chopra, S., Cun, Y.L.: Efficient learning of sparse representations with an energy-based model. In: Advances in Neural Information Processing Systems, pp. 1137\u20131144 (2007)","DOI":"10.7551\/mitpress\/7503.003.0147"},{"key":"988_CR19","doi-asserted-by":"crossref","unstructured":"Vincent, P., Larochelle, H., Bengio, Y., et al.: Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th International Conference on Machine Learning, pp. 1096\u20131103. ACM, New York (2008)","DOI":"10.1145\/1390156.1390294"},{"key":"988_CR20","unstructured":"Rifai, S., Vincent, P., Muller, X., et al.: Contractive auto-encoders: explicit invariance during feature extraction. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp. 833\u2013840 (2011)"},{"key":"988_CR21","unstructured":"Konda, K., Memisevic, R., Krueger, D.: Zero-bias autoencoders and the benefits of co-adapting features. Stat 1050: 13 (2014)"},{"key":"988_CR22","unstructured":"Arora, S., et al.: Simple, efficient, and neural algorithms for sparse coding. arXiv preprint arXiv:1503.00778 (2015)"},{"key":"988_CR23","unstructured":"Yang, J, et al.: Linear spatial pyramid matching using sparse coding for image classification. In: IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE, Washington (2009)"},{"issue":"1","key":"988_CR24","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1109\/TIP.2017.2755766","volume":"27","author":"X Lu","year":"2018","unstructured":"Lu, X., Chen, Y., Li, X.: Hierarchical recurrent neural hashing for image retrieval with hierarchical convolutional features. IEEE Trans. Image Process. 27(1), 106\u2013120 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"988_CR25","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1109\/TIP.2017.2754941","volume":"27","author":"W Wang","year":"2018","unstructured":"Wang, W., Shen, J., Shao, L.: Video salient object detection via fully convolutional networks. IEEE Trans. Image Process. 27(1), 38\u201349 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"988_CR26","doi-asserted-by":"publisher","first-page":"12133","DOI":"10.1007\/s11042-016-4142-3","volume":"76","author":"X Zhao","year":"2017","unstructured":"Zhao, X., Ding, G.: Query expansion for object retrieval with active learning using BoW and CNN feature. Multimed. Tools Appl. 76(9), 12133\u201312147 (2017)","journal-title":"Multimed. Tools Appl."},{"issue":"5","key":"988_CR27","doi-asserted-by":"publisher","first-page":"2368","DOI":"10.1109\/TIP.2017.2787612","volume":"27","author":"W Wang","year":"2017","unstructured":"Wang, W., Shen, J.: Deep visual attention prediction. IEEE Trans. Image Process. 27(5), 2368\u20132378 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"988_CR28","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1109\/MSP.2017.2749125","volume":"35","author":"J Han","year":"2018","unstructured":"Han, J., Zhang, D., Cheng, G., Liu, N., Xu, D.: Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Process. Mag. 35(1), 84\u2013100 (2018)","journal-title":"IEEE Signal Process. Mag."},{"issue":"1","key":"988_CR29","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1109\/TIP.2016.2627801","volume":"26","author":"X Lu","year":"2017","unstructured":"Lu, X., Zheng, X., Li, X.: Latent semantic minimal hashing for image retrieval. IEEE Trans. Image Process. 26(1), 355\u2013368 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"988_CR30","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.neucom.2017.01.055","volume":"257","author":"G Ding","year":"2017","unstructured":"Ding, G., et al.: Large-scale image retrieval with sparse embedded hashing. Neurocomputing 257, 24\u201336 (2017)","journal-title":"Neurocomputing"},{"key":"988_CR31","first-page":"1","volume":"99","author":"J Han","year":"2017","unstructured":"Han, J., Cheng, G., Li, Z., Zhang, D.: A unified metric learning-based framework for co-saliency detection. IEEE Trans. Circuits Syst. Video Technol. 99, 1\u20131 (2017)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"5","key":"988_CR32","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1109\/TPAMI.2016.2567393","volume":"39","author":"D Zhang","year":"2016","unstructured":"Zhang, D., Meng, D., Han, J.: Co-saliency detection via a self-paced multiple-instance learning framework. IEEE Trans. Pattern Anal. Mach. Intell. 39(5), 865\u2013878 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"988_CR33","doi-asserted-by":"crossref","unstructured":"Munajat, M.D.E., Widyantoro, D.H., Munir, R.: Road detection system based on RGB histogram filterization and boundary classifier. In: International Conference on Advanced Computer Science and Information Systems, pp. 195\u2013200. IEEE, Washington (2016)","DOI":"10.1109\/ICACSIS.2015.7415163"},{"issue":"4","key":"988_CR34","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1049\/ip-vis:20000630","volume":"147","author":"J Berens","year":"2000","unstructured":"Berens, J., Finlayson, G.D., Qiu, G.: Image indexing using compressed colour histograms. IEE Proc. Vis. Image Signal Process. 147(4), 349\u2013355 (2000)","journal-title":"IEE Proc. Vis. Image Signal Process."},{"issue":"2\u20133","key":"988_CR35","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1023\/A:1008018015948","volume":"31","author":"B Ginneken Van","year":"1999","unstructured":"Van Ginneken, B., Koenderink, J.J., Dana, K.J.: Texture histograms as a function of irradiation and viewing direction[J]. Int. J. Comput. Vis. 31(2\u20133), 169\u2013184 (1999)","journal-title":"Int. J. Comput. Vis."},{"issue":"2","key":"988_CR36","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. J. Comput. Vis. 60(2), 91\u2013110 (2004)","journal-title":"J. Comput. Vis."},{"key":"988_CR37","doi-asserted-by":"crossref","unstructured":"van de Sande, K., Gevers, T., Snoek, C.: Evaluation of color descriptors for object and scene recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp.\u00a01\u20138. IEEE, Anchorage (2008)","DOI":"10.1109\/CVPR.2008.4587658"},{"key":"988_CR38","doi-asserted-by":"crossref","unstructured":"Bosch, A., Zisserman, A., Munoz, X.: Representing shape with a spatial pyramid kernel. In: Proceedings of ACM International Conference on Image and Video Retrieval, pp. 672\u2013679. ACM, New York (2007)","DOI":"10.1145\/1282280.1282340"},{"issue":"3","key":"988_CR39","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1145\/1276377.1276382","volume":"26","author":"H James","year":"2007","unstructured":"James, H., et al.: Scene completion using millions of photographs. ACM Trans. Graph. 26(3), 4 (2007)","journal-title":"ACM Trans. Graph."},{"key":"988_CR40","doi-asserted-by":"crossref","unstructured":"Wang, W., Shen, J.: Deep cropping via attention box prediction and aesthetics assessment. In: IEEE International Conference on Computer Vision (2017)","DOI":"10.1109\/ICCV.2017.240"},{"issue":"2","key":"988_CR41","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/TKDE.2003.1185844","volume":"15","author":"MA Rodr\u00edguez","year":"2003","unstructured":"Rodr\u00edguez, M.A., Egenhofer, M.J.: Determining semantic similarity among entity classes from different ontologies. IEEE Trans. Knowl. Data Eng. 15(2), 442\u2013456 (2003)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"988_CR42","unstructured":"Mihalcea, R., Corley, C., Strapparava, C.: Corpus-based and knowledge-based measures of text semantic similarity. In: AAAI 2006, vol. 6, pp. 775\u2013780"},{"key":"988_CR43","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7287.001.0001","volume-title":"WordNet","author":"C Fellbaum","year":"1998","unstructured":"Fellbaum, C.: WordNet. Wiley, New York (1998)"},{"issue":"4","key":"988_CR44","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1007\/s00371-014-0931-8","volume":"31","author":"H Wu","year":"2015","unstructured":"Wu, H., Miao, Z., Wang, Y., et al.: Optimized recognition with few instances based on semantic distance. Vis. Comput. 31(4), 367\u2013375 (2015)","journal-title":"Vis. Comput."},{"issue":"4","key":"988_CR45","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/5254.708428","volume":"13","author":"MA Hearst","year":"1998","unstructured":"Hearst, M.A., Dumais, S.T., Osman, E., et al.: Support vector machines. IEEE Intell. Syst. Appl. 13(4), 18\u201328 (1998)","journal-title":"IEEE Intell. Syst. Appl."},{"key":"988_CR46","unstructured":"Vapnik, V.: Principles of risk minimization for learning theory. In: NIPS, pp. 831\u2013838 (1991)"},{"key":"988_CR47","doi-asserted-by":"crossref","unstructured":"Keogh, E., Mueen, A.: Curse of dimensionality. In: Encyclopedia of Machine Learning, pp. 257\u2013258. Springer, Boston, MA (2011)","DOI":"10.1007\/978-0-387-30164-8_192"},{"issue":"4","key":"988_CR48","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1016\/j.eswa.2004.12.008","volume":"28","author":"JH Min","year":"2005","unstructured":"Min, J.H., Lee, Y.C.: Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters. Expert Syst. Appl. 28(4), 603\u2013614 (2005)","journal-title":"Expert Syst. Appl."},{"key":"988_CR49","doi-asserted-by":"crossref","unstructured":"Sahami, M., Heilman, T.D.: A web-based kernel function for measuring the similarity of short text snippets. In: Proceedings of the 15th International Conference on World Wide Web, pp. 377\u2013386. ACM, London (2006)","DOI":"10.1145\/1135777.1135834"},{"issue":"7","key":"988_CR50","doi-asserted-by":"publisher","first-page":"1667","DOI":"10.1162\/089976603321891855","volume":"15","author":"SS Keerthi","year":"2003","unstructured":"Keerthi, S.S., Lin, C.J.: Asymptotic behaviors of support vector machines with Gaussian kernel. Neural Comput. 15(7), 1667\u20131689 (2003)","journal-title":"Neural Comput."},{"key":"988_CR51","doi-asserted-by":"crossref","unstructured":"Venu, N, Anuradha, B.: Integration of hyperbolic tangent and Gaussian kernels for fuzzy C-means algorithm with spatial information for MRI segmentation. In: 2013 Fifth International Conference on Advanced Computing (ICoAC), pp. 280\u2013285. IEEE, Washington (2013)","DOI":"10.1109\/ICoAC.2013.6921964"},{"issue":"5","key":"988_CR52","doi-asserted-by":"publisher","first-page":"1187","DOI":"10.1007\/s00500-014-1332-7","volume":"19","author":"F Kuang","year":"2015","unstructured":"Kuang, F., Zhang, S., Jin, Z., et al.: A novel SVM by combining kernel principal component analysis and improved chaotic particle swarm optimization for intrusion detection. Soft. Comput. 19(5), 1187\u20131199 (2015)","journal-title":"Soft. Comput."},{"key":"988_CR53","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1016\/j.neucom.2015.10.018","volume":"174","author":"X Gao","year":"2016","unstructured":"Gao, X., Hou, J.: An improved SVM integrated GS-PCA fault diagnosis approach of Tennessee Eastman process. Neurocomputing 174, 906\u2013911 (2016)","journal-title":"Neurocomputing"},{"issue":"5","key":"988_CR54","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1016\/j.compbiomed.2013.01.020","volume":"43","author":"A Subasi","year":"2013","unstructured":"Subasi, A.: Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. Comput. Biol. Med. 43(5), 576\u2013586 (2013)","journal-title":"Comput. Biol. Med."},{"key":"988_CR55","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.neucom.2012.07.017","volume":"101","author":"S Ch","year":"2013","unstructured":"Ch, S., Anand, N., Panigrahi, B.K., et al.: Streamflow forecasting by SVM with quantum behaved particle swarm optimization. Neurocomputing 101, 18\u201323 (2013)","journal-title":"Neurocomputing"},{"key":"988_CR56","doi-asserted-by":"crossref","unstructured":"Wang, G., Forsyth, D., Hoiem, D.: Comparative object similarity for improved recognition with few or no examples. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3525\u20133532. IEEE, Washington (2010)","DOI":"10.1109\/CVPR.2010.5539955"},{"issue":"3","key":"988_CR57","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1049\/iet-cvi.2014.0094","volume":"9","author":"H Wu","year":"2015","unstructured":"Wu, H., Miao, Z., Chen, J., et al.: Recognition improvement through the optimisation of learning instances. IET Comput. Vis. 9(3), 419\u2013427 (2015)","journal-title":"IET Comput. Vis."},{"issue":"15","key":"988_CR58","doi-asserted-by":"publisher","first-page":"16749","DOI":"10.1007\/s11042-016-3950-9","volume":"76","author":"Y Li","year":"2016","unstructured":"Li, Y., Bie, R., Zhang, C., et al.: Optimized learning instance-based image retrieval. Multimed. Tools Appl. 76(15), 16749\u201316766 (2016)","journal-title":"Multimed. Tools Appl."},{"key":"988_CR59","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1016\/j.jvcir.2018.06.021","volume":"55","author":"H Wu","year":"2018","unstructured":"Wu, H., Li, Y., Bi, X., et al.: Joint entropy based learning model for image retrieval. J V Commun Image Represent 55, 415\u2013423 (2018)","journal-title":"J V Commun Image Represent"},{"issue":"4","key":"988_CR60","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1109\/TMM.2016.2638207","volume":"19","author":"X Qian","year":"2017","unstructured":"Qian, X., Wang, H., Zhao, Y., Hou, X., Hong, R., Wang, M., Tang, Y.Y.: Image location inference by multisaliency enhancement. IEEE Trans. Multimed. 19(4), 813\u2013821 (2017)","journal-title":"IEEE Trans. Multimed."},{"issue":"10","key":"988_CR61","doi-asserted-by":"publisher","first-page":"1937","DOI":"10.1109\/JPROC.2017.2731600","volume":"105","author":"X Qian","year":"2017","unstructured":"Qian, X., Xiaoqiang, L., Han, J., Bo, D., Li, X.: On combining social media and spatial technology for POI cognition and image localization. Proc. IEEE 105(10), 1937\u20131952 (2017)","journal-title":"Proc. IEEE"},{"issue":"3","key":"988_CR62","doi-asserted-by":"publisher","first-page":"1178","DOI":"10.1109\/TIP.2017.2769454","volume":"27","author":"X Qian","year":"2018","unstructured":"Qian, X., Li, C., Lan, K., Hou, X., Li, Z., Han, J.: POI summarization by aesthetics evaluation from crowd source social media. IEEE Trans. Image Process. 27(3), 1178\u20131189 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"988_CR63","doi-asserted-by":"publisher","first-page":"1639","DOI":"10.1109\/TIP.2017.2781424","volume":"27","author":"J Han","year":"2018","unstructured":"Han, J., Quan, R., Zhang, D., Nie, F.: Robust object co-segmentation using background prior. IEEE Trans. Image Process. 27(4), 1639\u20131651 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"988_CR64","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1145\/1618452.1618493","volume":"28","author":"K Subr","year":"2009","unstructured":"Subr, K., Soler, C., Durand, F.: Edge-preserving multiscale image decomposition based on local extrema. ACM Trans. Graph. (TOG) 28(5), 147 (2009)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"988_CR65","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1016\/j.jvcir.2016.04.008","volume":"38","author":"H Wu","year":"2016","unstructured":"Wu, H., Li, Y., Miao, Z., et al.: A new sampling algorithm for high-quality image matting. J. Vis. Commun. Image Represent. 38, 573\u2013581 (2016)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"C","key":"988_CR66","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.neucom.2014.12.088","volume":"159","author":"H Wu","year":"2015","unstructured":"Wu, H., Miao, Z., Wang, Y., et al.: Image completion with multi-image based on entropy reduction. Neurocomputing 159(C), 157\u2013171 (2015)","journal-title":"Neurocomputing"},{"issue":"11","key":"988_CR67","doi-asserted-by":"publisher","first-page":"1530","DOI":"10.1109\/83.641413","volume":"6","author":"L Shafarenko","year":"1997","unstructured":"Shafarenko, L., Petrou, M., Kittler, J.: Automatic watershed segmentation of randomly textured color images. IEEE Trans. Image Process. 6(11), 1530\u20131544 (1997)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"988_CR68","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s11263-007-0090-8","volume":"77","author":"BC Russell","year":"2008","unstructured":"Russell, B.C., Torralba, A., Murphy, K.P., et al.: LabelMe: a database and web-based tool for image annotation[J]. Int. J. Comput. Vis. 77(1), 157\u2013173 (2008)","journal-title":"Int. J. Comput. Vis."},{"key":"988_CR69","unstructured":"Griffin, G., Holub, A., Perona, P.: Caltech-256 object category dataset (2007)"},{"key":"988_CR70","unstructured":"Deng, J., Dong, W., Socher, R., et al.: Imagenet: a large-scale hierarchical image database. In: IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009, pp. 248\u2013255. IEEE, Washington (2009)"},{"key":"988_CR71","doi-asserted-by":"crossref","unstructured":"Radenovi\u0107, F., Tolias, G., Chum, O.: CNN image retrieval learns from BoW: unsupervised fine-tuning with hard examples. In: European Conference on Computer Vision, pp. 3\u201320. Springer, Cham (2016)","DOI":"10.1007\/978-3-319-46448-0_1"},{"key":"988_CR72","doi-asserted-by":"publisher","first-page":"851","DOI":"10.1016\/j.ins.2015.05.012","volume":"329","author":"I Dimitrovski","year":"2016","unstructured":"Dimitrovski, I., Kocev, D., Loskovska, S., et al.: Improving bag-of-visual-words image retrieval with predictive clustering trees. Inf. Sci. 329, 851\u2013865 (2016)","journal-title":"Inf. Sci."},{"issue":"4","key":"988_CR73","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1109\/TCYB.2014.2336697","volume":"45","author":"J Yu","year":"2015","unstructured":"Yu, J., et al.: Learning to rank using user clicks and visual features for image retrieval. IEEE Trans. Cybern. 45(4), 767\u2013779 (2015)","journal-title":"IEEE Trans. Cybern."},{"key":"988_CR74","unstructured":"Vedaldi, A., Zisserman, A.: Image classification practical. http:\/\/www.robots.ox.ac.uk\/~vgg\/share\/practical-image-classification.htm (2011)"},{"key":"988_CR75","doi-asserted-by":"crossref","unstructured":"Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2. IEEE, Washington (2006)","DOI":"10.1109\/CVPR.2006.68"},{"key":"988_CR76","doi-asserted-by":"crossref","unstructured":"Nowak, E., Jurie, F., Triggs, B.: Sampling strategies for bag-of-features image classification. In: Computer Vision\u2014ECCV 2006, pp. 490\u2013503 (2006)","DOI":"10.1007\/11744085_38"}],"container-title":["Machine Vision and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00138-018-0988-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-018-0988-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-018-0988-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T22:26:16Z","timestamp":1775255176000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00138-018-0988-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,30]]},"references-count":76,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,2]]}},"alternative-id":["988"],"URL":"https:\/\/doi.org\/10.1007\/s00138-018-0988-x","relation":{},"ISSN":["0932-8092","1432-1769"],"issn-type":[{"value":"0932-8092","type":"print"},{"value":"1432-1769","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,30]]},"assertion":[{"value":"9 November 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}