{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:24:15Z","timestamp":1740122655086,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T00:00:00Z","timestamp":1617321600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T00:00:00Z","timestamp":1617321600000},"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":[[2021,11]]},"DOI":"10.1007\/s10489-021-02338-x","type":"journal-article","created":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T04:06:40Z","timestamp":1617336400000},"page":"8349-8364","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Joint latent low-rank and non-negative induced sparse representation for face recognition"],"prefix":"10.1007","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0098-1668","authenticated-orcid":false,"given":"Mingna","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhigang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenwen","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,2]]},"reference":[{"key":"2338_CR1","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1016\/j.patcog.2018.12.023","volume":"88","author":"J Xu","year":"2019","unstructured":"Xu J, An W, Zhang L, Zhang D (2019) Sparse, collaborative, or nonnegative representation: which helps pattern classification? Pattern Recogn 88:679\u2013688","journal-title":"Pattern Recogn"},{"key":"2338_CR2","doi-asserted-by":"crossref","unstructured":"Deng W, Hu J, Guo J (2013) In defense of sparsity based face recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 399\u2013406","DOI":"10.1109\/CVPR.2013.58"},{"issue":"5","key":"2338_CR3","doi-asserted-by":"publisher","first-page":"1080","DOI":"10.1109\/TNNLS.2015.2436951","volume":"27","author":"P Zhou","year":"2015","unstructured":"Zhou P, Lin Z, Zhang C (2015) Integrated low-rank-based discriminative feature learning for recognition. IEEE Transactions on Neural Networks and Learning Systems 27(5):1080\u20131093","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"12","key":"2338_CR4","doi-asserted-by":"publisher","first-page":"2051","DOI":"10.1109\/TIFS.2014.2361936","volume":"9","author":"Y Li","year":"2017","unstructured":"Li Y, Liu J, Lu H, Ma S (2017) Learning robust face representation with classwise block-diagonal structure. IEEE Transactions on Information Forensics and Security 9(12):2051\u20132062","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"2338_CR5","doi-asserted-by":"publisher","first-page":"104823","DOI":"10.1016\/j.knosys.2019.06.031","volume":"187","author":"H Du","year":"2020","unstructured":"Du H, Ma L, Li G, Wang S (2020) Low-rank graph preserving discriminative dictionary learning for image recognition. Knowledge-Based Systems 187:104823","journal-title":"Knowledge-Based Systems"},{"key":"2338_CR6","doi-asserted-by":"publisher","first-page":"105768","DOI":"10.1016\/j.knosys.2020.105768","volume":"196","author":"X Yang","year":"2020","unstructured":"Yang X, Jiang X, Tian C, Wang P, Zhou F, Fujita H (2020) Inverse projection group sparse representation for tumor classification: A low rank variation dictionary approach. Knowledge-Based Systems 196:105768","journal-title":"Knowledge-Based Systems"},{"key":"2338_CR7","doi-asserted-by":"publisher","first-page":"107758","DOI":"10.1016\/j.patcog.2020.107758","volume":"113","author":"J Lu","year":"2020","unstructured":"Lu J, Wang H, Zhou J, Chen Y, Lai Z, Hu Q (2020) Low-rank adaptive graph embedding for unsupervised feature extraction. Pattern Recognition 113:107758","journal-title":"Pattern Recognition"},{"key":"2338_CR8","doi-asserted-by":"publisher","first-page":"106199","DOI":"10.1016\/j.knosys.2020.106199","volume":"204","author":"W Zhu","year":"2020","unstructured":"Zhu W, Peng B (2020) Sparse and low-rank regularized deep subspace clustering. Knowledge-Based Systems 204:106199","journal-title":"Knowledge-Based Systems"},{"key":"2338_CR9","doi-asserted-by":"publisher","first-page":"8668","DOI":"10.1109\/ACCESS.2019.2960928","volume":"8","author":"S Liu","year":"2019","unstructured":"Liu S, Li L, Jin M, Hou S, Peng Y (2019) Optimized coefficient vector and sparse representation-based classification method for face recognition. IEEE Access 8:8668\u20138674","journal-title":"IEEE Access"},{"key":"2338_CR10","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.neucom.2019.09.025","volume":"373","author":"M Liao","year":"2020","unstructured":"Liao M, Xiaodong G u (2020) Face recognition approach by subspace extended sparse representation and discriminative feature learning. Neurocomputing 373:35\u201349","journal-title":"Neurocomputing"},{"issue":"2","key":"2338_CR11","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"J Wright","year":"2009","unstructured":"Wright J, Yang AY, Ganesh A, Shankar Sastry S, Yi M a (2009) Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(2):210\u2013227","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"9","key":"2338_CR12","doi-asserted-by":"publisher","first-page":"1864","DOI":"10.1109\/TPAMI.2012.30","volume":"34","author":"W Deng","year":"2012","unstructured":"Deng W, Hu J, Guo J (2012) Extended src: under-sampled face recognition via intraclass variant dictionary. IEEE Trans Pattern Anal Mach Intell 34(9):1864\u20131870","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2338_CR13","unstructured":"Zhang L, Yang M, Feng X, Ma Y, Zhang D (2012) Collaborative representation based classification for face recognition. arXiv:1204.2358"},{"issue":"1","key":"2338_CR14","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1109\/TIFS.2018.2849883","volume":"14","author":"S Yang","year":"2019","unstructured":"Yang S, Zhang L, He L, Wen Y (2019) Sparse low-rank component-based representation for face recognition with low-quality images. IEEE Transactions on Information Forensics and Security 14(1):251\u2013261","journal-title":"IEEE Transactions on Information Forensics and Security"},{"issue":"5","key":"2338_CR15","doi-asserted-by":"publisher","first-page":"2545","DOI":"10.1109\/TIP.2017.2675341","volume":"26","author":"Y Gao","year":"2017","unstructured":"Gao Y, Ma J, Yuille AL (2017) Semi-supervised sparse representation based classification for face recognition with insufficient labeled samples. IEEE Trans Image Process 26(5):2545\u20132560","journal-title":"IEEE Trans Image Process"},{"key":"2338_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ins.2019.08.060","volume":"508","author":"T Deng","year":"2020","unstructured":"Deng T, Ye D, Ma R, Fujita H, Xiong L (2020) Low-rank local tangent space embedding for subspace clustering. Inf Sci 508:1\u201321","journal-title":"Inf Sci"},{"key":"2338_CR17","unstructured":"Liu G, Lin Z, Yong Y u (2010) Robust subspace segmentation by low-rank representation. In: International conference on machine learning"},{"key":"2338_CR18","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.patcog.2017.05.003","volume":"70","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Xiang M, Yang B (2017) Low-rank preserving embedding. Pattern Recogn 70:112\u2013125","journal-title":"Pattern Recogn"},{"key":"2338_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIP.2017.2787262","volume":"27","author":"L Xie","year":"2018","unstructured":"Xie L, Yin M, Yin X, Liu Y, Yin G (2018) Low-rank sparse preserving projections for dimensionality reduction. IEEE Trans Image Process 27:1\u20131","journal-title":"IEEE Trans Image Process"},{"key":"2338_CR20","doi-asserted-by":"crossref","unstructured":"Liu G, Yan S (2011) Latent low-rank representation for subspace segmentation and feature extraction. In: 2011 IEEE international conference on computer vision (ICCV). IEEE, p 2011","DOI":"10.1109\/ICCV.2011.6126422"},{"key":"2338_CR21","doi-asserted-by":"crossref","unstructured":"Wang L, Zhang Z, Li S, Liu G, Hou C, Qin J (2018) Similarity-adaptive latent low-rank representation for robust data representation. In: Pacific rim international conference on artificial intelligence. Springer, pp 71\u201384","DOI":"10.1007\/978-3-319-97304-3_6"},{"key":"2338_CR22","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.neucom.2019.06.073","volume":"362","author":"Z Liu","year":"2019","unstructured":"Liu Z, Ou W, Lu W, Wang L (2019) Discriminative feature extraction based on sparse and low-rank representation. Neurocomputing 362:129\u2013138","journal-title":"Neurocomputing"},{"key":"2338_CR23","doi-asserted-by":"publisher","first-page":"2479","DOI":"10.1016\/j.neucom.2017.11.021","volume":"275","author":"S Yu","year":"2018","unstructured":"Yu S, Yiquan W (2018) Subspace clustering based on latent low rank representation with frobenius norm minimization. Neurocomputing 275:2479\u20132489","journal-title":"Neurocomputing"},{"key":"2338_CR24","doi-asserted-by":"publisher","first-page":"5228","DOI":"10.1109\/TNNLS.2018.2796133","volume":"29","author":"X Fang","year":"2018","unstructured":"Fang X, Han N, Wu J, Xu Y, Yang J, Wong WK, Li X (2018) Approximate low-rank projection learning for feature extraction. IEEE Transactions on Neural Networks and Learning Systems 29:5228\u20135241","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"99","key":"2338_CR25","first-page":"1","volume":"PP","author":"Z Ren","year":"2019","unstructured":"Ren Z, Sun Q, Wu B, Zhang X, Yan W (2019) Learning latent low-rank and sparse embedding for robust image feature extraction. IEEE Transactions on Image Processing PP(99):1\u20131","journal-title":"IEEE Transactions on Image Processing"},{"key":"2338_CR26","unstructured":"Lin Z, Chen M, Ma Y (2010) The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. arXiv:1009.5055"},{"issue":"13","key":"2338_CR27","doi-asserted-by":"publisher","first-page":"9081","DOI":"10.1007\/s00521-019-04419-y","volume":"32","author":"Z Ren","year":"2020","unstructured":"Ren Z, Sun Q, Yang C (2020) Nonnegative discriminative encoded nearest points for image set classification. Neural Comput Applic 32(13):9081\u20139092","journal-title":"Neural Comput Applic"},{"issue":"15","key":"2338_CR28","doi-asserted-by":"publisher","first-page":"8861","DOI":"10.1007\/s11042-014-2257-y","volume":"75","author":"B Shen","year":"2016","unstructured":"Shen B, Liu BD, Wang Q (2016) Elastic net regularized dictionary learning for image classification. Multimedia Tools and Applications 75(15):8861\u20138874","journal-title":"Multimedia Tools and Applications"},{"issue":"4","key":"2338_CR29","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1137\/080738970","volume":"20","author":"J-F Cai","year":"2010","unstructured":"Cai J-F, Cand\u00e8s EJ, Shen Z (2010) A singular value thresholding algorithm for matrix completion. SIAM Journal on Optimization 20(4):1956\u20131982","journal-title":"SIAM Journal on Optimization"},{"issue":"6","key":"2338_CR30","doi-asserted-by":"publisher","first-page":"2905","DOI":"10.1109\/TIP.2017.2691543","volume":"26","author":"WK Wong","year":"2017","unstructured":"Wong WK, Lai Z, Wen J, Fang X, Yuwu L u (2017) Low-rank embedding for robust image feature extraction. IEEE Trans Image Process 26(6):2905\u20132917","journal-title":"IEEE Trans Image Process"},{"key":"2338_CR31","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.knosys.2017.03.002","volume":"124","author":"S Wang","year":"2017","unstructured":"Wang S, Wang H (2017) Unsupervised feature selection via low-rank approximation and structure learning. Knowl-Based Syst 124:70\u201379","journal-title":"Knowl-Based Syst"},{"key":"2338_CR32","unstructured":"Martinez AM (1998) The ar face database. CVC Technical Report24"},{"issue":"2605","key":"2338_CR33","first-page":"2579","volume":"9","author":"VDM Laurens","year":"2008","unstructured":"Laurens VDM, Hinton G (2008) Visualizing data using t-sne. J Mach Learn Res 9 (2605):2579\u20132605","journal-title":"J Mach Learn Res"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-02338-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-021-02338-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-021-02338-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,7]],"date-time":"2021-10-07T06:09:28Z","timestamp":1633586968000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-021-02338-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,2]]},"references-count":33,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2021,11]]}},"alternative-id":["2338"],"URL":"https:\/\/doi.org\/10.1007\/s10489-021-02338-x","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2021,4,2]]},"assertion":[{"value":"6 March 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 April 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}