{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T14:08:31Z","timestamp":1765807711514,"version":"3.41.2"},"reference-count":61,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T00:00:00Z","timestamp":1560988800000},"content-version":"vor","delay-in-days":170,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61771079","61571069","61801072"],"award-info":[{"award-number":["61771079","61571069","61801072"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2019,1]]},"abstract":"<jats:p>Na\u00efve sparse representation has stability problem due to its unsupervised nature, which is not preferred for classification tasks. For this problem, this paper presents a novel representation learning method named classification\u2010oriented local representation (CoLR) for image recognition. The core idea of CoLR is to find the most relevant training classes and samples with test sample by taking the merits of class\u2010wise sparseness weighting, sample locality, and label prior. The proposed representation strategy can not only promote a classification\u2010oriented representation, but also boost a locality adaptive representation within the selected training classes. The CoLR model is efficiently solved by Augmented Lagrange Multiplier (ALM) scheme based on a variable splitting strategy. Then, the performance of the proposed model is evaluated on benchmark face datasets and deep object features. Specifically, the deep features of the object dataset are obtained by a well\u2010trained convolutional neural network (CNN) with five convolutional layers and three fully connected layers on the challenging ImageNet. Extensive experiments verify the superiority of CoLR in comparison with some state\u2010of\u2010the\u2010art models.<\/jats:p>","DOI":"10.1155\/2019\/7835797","type":"journal-article","created":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T23:31:23Z","timestamp":1561073483000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["CoLR: Classification\u2010Oriented Local Representation for Image Recognition"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9523-8094","authenticated-orcid":false,"given":"Tan","family":"Guo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5305-8543","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoheng","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8868-6913","authenticated-orcid":false,"given":"Zhiwei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2337-1483","authenticated-orcid":false,"given":"Fupeng","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,6,20]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2017.2772264"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2018.2796133"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.881945"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.217"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2013.2277780"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2810806"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs9080790"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2002.999679"},{"key":"e_1_2_9_9_2","doi-asserted-by":"crossref","unstructured":"AhonenT. HadidA. andPietikainenM. Face recognition with local binary patterns 3021 Proceedings of the 8th European Conference on Computer Vision (ECCV \u203204) May 2004 Prague Czech Republic Springer 469\u2013481 Lecture Notes in Computer Science https:\/\/doi.org\/10.1007\/978-3-540-24670-1_36.","DOI":"10.1007\/978-3-540-24670-1_36"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1162\/jocn.1991.3.1.71"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.598228"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017467"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/72.750575"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1114855"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.79"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.128"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_1"},{"key":"e_1_2_9_19_2","doi-asserted-by":"crossref","unstructured":"YangM. ZhangL. YangJ. andZhangD. Robust sparse coding for face recognition Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR \u203211) June 2011 Colorado Springs Colo USA IEEE 625\u2013632 https:\/\/doi.org\/10.1109\/CVPR.2011.5995393 2-s2.0-80052913149.","DOI":"10.1109\/CVPR.2011.5995393"},{"key":"e_1_2_9_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.06.022"},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2359453"},{"key":"e_1_2_9_22_2","doi-asserted-by":"crossref","unstructured":"ZhangL. YangM. andFengX. Sparse representation or collaborative representation: Which helps face recognition? Proceedings of the IEEE International Conference on Computer Vision (ICCV \u203211) November 2011 Barcelona Spain IEEE 471\u2013478 https:\/\/doi.org\/10.1109\/ICCV.2011.6126277 2-s2.0-84863011302.","DOI":"10.1109\/ICCV.2011.6126277"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.08.022"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.12.017"},{"key":"e_1_2_9_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2757923"},{"key":"e_1_2_9_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.04.006"},{"key":"e_1_2_9_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-017-9474-4"},{"key":"e_1_2_9_28_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-018-9809-5"},{"key":"e_1_2_9_29_2","unstructured":"MajumdarA.andWardR. K. Classification via group sparsity promoting regularization Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP \u203209) April 2009 Taiwan IEEE 861\u2013864 2-s2.0-70349192993."},{"key":"e_1_2_9_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2015.04.018"},{"key":"e_1_2_9_31_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2545249"},{"key":"e_1_2_9_32_2","unstructured":"YuK. ZhangT. andGongY. Nonlinear learning using local coordinate coding Proceedings of the 23rd Annual Conference on Neural Information Processing Systems December 2009 British Columbia Canada 2223\u20132231."},{"key":"e_1_2_9_33_2","doi-asserted-by":"crossref","unstructured":"WangJ. YangJ. YuK. LvF. HuangT. andGongY. Locality-constrained linear coding for image classification Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR \u203210) June 2010 San Francisco Calif USA IEEE 3360\u20133367 https:\/\/doi.org\/10.1109\/CVPR.2010.5540018 2-s2.0-77955996870.","DOI":"10.1109\/CVPR.2010.5540018"},{"key":"e_1_2_9_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2012.05.003"},{"key":"e_1_2_9_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2011.2138790"},{"key":"e_1_2_9_36_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-013-9333-6"},{"key":"e_1_2_9_37_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2013.09.004"},{"key":"e_1_2_9_38_2","doi-asserted-by":"crossref","unstructured":"ZhangN.andYangJ. K nearest neighbor based local sparse representation classifier Proceedings of the Chinese Conference on Pattern Recognition (CCPR \u203210) October 2010 Chongqing China IEEE 1\u20135 https:\/\/doi.org\/10.1109\/CCPR.2010.5659128.","DOI":"10.1109\/CCPR.2010.5659128"},{"key":"e_1_2_9_39_2","doi-asserted-by":"crossref","unstructured":"ChaoY. YehY. ChenY. LeeY. andWangY. F. Locality-constrained group sparse representation for robust face recognition Proceedings of the 18th IEEE International Conference on Image Processing (ICIP \u203211) September 2011 Brussels Belgium IEEE 11\u201314 https:\/\/doi.org\/10.1109\/ICIP.2011.6116666.","DOI":"10.1109\/ICIP.2011.6116666"},{"key":"e_1_2_9_40_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.05.012"},{"key":"e_1_2_9_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.881199"},{"key":"e_1_2_9_42_2","doi-asserted-by":"crossref","unstructured":"ZhangQ.andLiB. Discriminative K-SVD for dictionary learning in face recognition Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR \u203210) June 2010 San Francisco Claif USA IEEE 2691\u20132698 https:\/\/doi.org\/10.1109\/CVPR.2010.5539989 2-s2.0-77955998411.","DOI":"10.1109\/CVPR.2010.5539989"},{"key":"e_1_2_9_43_2","doi-asserted-by":"crossref","unstructured":"JiangZ. L. LinZ. andDavisL. S. Learning a discriminative dictionary for sparse coding via label consistent K-SVD Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR \u203211) June 2011 Colorado Springs Colo USA IEEE 1697\u20131704 https:\/\/doi.org\/10.1109\/cvpr.2011.5995354 2-s2.0-80052901219.","DOI":"10.1109\/CVPR.2011.5995354"},{"key":"e_1_2_9_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2508025"},{"key":"e_1_2_9_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2017.2740224"},{"key":"e_1_2_9_46_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2018.04.006"},{"key":"e_1_2_9_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2017.2653184"},{"key":"e_1_2_9_48_2","unstructured":"GuS. ZhangL. ZuoW. andFengX. Projective dictionary pair learning for pattern classification Proceedings of the 28th Annual Conference on Neural Information Processing Systems (NIPS \u203214) December 2014 793\u2013801 2-s2.0-84937873657."},{"key":"e_1_2_9_49_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2550016"},{"key":"e_1_2_9_50_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2017.2712801"},{"key":"e_1_2_9_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.927464"},{"key":"e_1_2_9_52_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1251154"},{"key":"e_1_2_9_53_2","unstructured":"MartinezA.andBenaventeR. The AR face database CVC Technical Report 1998 no. 24."},{"key":"e_1_2_9_54_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1177153"},{"key":"e_1_2_9_55_2","doi-asserted-by":"publisher","DOI":"10.1002\/cpa.20132"},{"key":"e_1_2_9_56_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00532.x"},{"volume-title":"Constrained Optimization and Lagrange Multiplier Methods","year":"1996","author":"Bertsekas D. P.","key":"e_1_2_9_57_2"},{"key":"e_1_2_9_58_2","unstructured":"LinZ. ChenM. WuL. andMaY. The augmented Lagrange multiplier method for exact recovery of corrupted low-rank matrices UIUC 2009 no. UILU-ENG-09-2215."},{"key":"e_1_2_9_59_2","doi-asserted-by":"crossref","unstructured":"DengW. YinW. andZhangY. Group sparse optimization by alternating direction method Defense Technical Information Center 2011 no. TR11-06 Department of Computational and Applied Mathematics Rice University Houston Tex USA https:\/\/doi.org\/10.21236\/ADA585746.","DOI":"10.21236\/ADA585746"},{"key":"e_1_2_9_60_2","unstructured":"KrizhevskyA. SutskeverI. andHintonG. E. Imagenet classification with deep convolutional neural networks Proceedings of the 26th Annual Conference on Neural Information Processing Systems (NIPS \u203212) December 2012 Lake Tahoe Nev USA 1097\u20131105 2-s2.0-84876231242."},{"key":"e_1_2_9_61_2","unstructured":"DonahueJ. JiaY. VinyalsO. HoffmanJ. ZhangN. TzengE. andDarrellT. DeCAF: a deep convolutional activation feature for generic visual recognition Proceedings of the 31st International Conference on Machine Learning (ICML \u203214) June 2014 Beijing China 988\u2013996 2-s2.0-84919881041."}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2019\/7835797.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2019\/7835797.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2019\/7835797","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T11:28:42Z","timestamp":1723030122000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2019\/7835797"}},"subtitle":[],"editor":[{"given":"Michele","family":"Scarpiniti","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2019,1]]},"references-count":61,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,1]]}},"alternative-id":["10.1155\/2019\/7835797"],"URL":"https:\/\/doi.org\/10.1155\/2019\/7835797","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"type":"print","value":"1076-2787"},{"type":"electronic","value":"1099-0526"}],"subject":[],"published":{"date-parts":[[2019,1]]},"assertion":[{"value":"2019-02-28","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-05-29","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-06-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"7835797"}}