{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T21:08:39Z","timestamp":1773868119992,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"28","license":[{"start":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T00:00:00Z","timestamp":1690156800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T00:00:00Z","timestamp":1690156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology","award":["NRF- 2021R1A2C1093425"],"award-info":[{"award-number":["NRF- 2021R1A2C1093425"]}]},{"name":"National Research Foundation of Korea (NRF) under the program of Basic Research Laboratory","award":["NRF-2022R1A4A2000748"],"award-info":[{"award-number":["NRF-2022R1A4A2000748"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s00521-023-08801-9","type":"journal-article","created":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T13:02:31Z","timestamp":1690203751000},"page":"20697-20715","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Face photo-sketch recognition based on multi-directional line features projection"],"prefix":"10.1007","volume":"35","author":[{"given":"Jooyoung","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiping","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghyun","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3736-003X","authenticated-orcid":false,"given":"Kar-Ann","family":"Toh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,24]]},"reference":[{"key":"8801_CR1","doi-asserted-by":"crossref","unstructured":"Chalabi NE, Attia A, Bouziane A, Hassaballah M, Akhtar Z (2022) Recent trends in face recognition using metaheuristic optimization. In: Handbook of nature-inspired optimization algorithms: the state of the art, Volume II, Solving Constrained Single Objective Real-Parameter Optimization Problems. Springer, pp 85\u2013112","DOI":"10.1007\/978-3-031-07516-2_5"},{"issue":"11","key":"8801_CR2","doi-asserted-by":"publisher","first-page":"1586","DOI":"10.1109\/LSP.2017.2749266","volume":"24","author":"C Galea","year":"2017","unstructured":"Galea C, Farrugia RA (2017) Forensic face photo-sketch recognition using a deep learning-based architecture. IEEE Signal Process Lett 24(11):1586\u20131590","journal-title":"IEEE Signal Process Lett"},{"issue":"11","key":"8801_CR3","doi-asserted-by":"publisher","first-page":"1955","DOI":"10.1109\/TPAMI.2008.222","volume":"31","author":"X Wang","year":"2009","unstructured":"Wang X, Tang X (2009) Face photo-sketch synthesis and recognition. IEEE Trans Pattern Anal Mach Intell 31(11):1955\u20131967","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"8801_CR4","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1049\/iet-cvi.2014.0084","volume":"9","author":"M Hassaballah","year":"2015","unstructured":"Hassaballah M, Aly S (2015) Face recognition: challenges, achievements and future directions. IET Comput Vis 9(4):614\u2013626","journal-title":"IET Comput Vis"},{"issue":"3","key":"8801_CR5","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1007\/s11263-016-0933-2","volume":"122","author":"MS Sarfraz","year":"2017","unstructured":"Sarfraz MS, Stiefelhagen R (2017) Deep perceptual mapping for cross-modal face recognition. Int J Comput Vis 122(3):426\u2013438","journal-title":"Int J Comput Vis"},{"key":"8801_CR6","doi-asserted-by":"crossref","unstructured":"Zhang W, Wang X, Tang X (2011) Coupled information-theoretic encoding for face photo-sketch recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE, pp 513\u2013520","DOI":"10.1109\/CVPR.2011.5995324"},{"issue":"3","key":"8801_CR7","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1109\/TPAMI.2010.180","volume":"33","author":"B Klare","year":"2010","unstructured":"Klare B, Li Z, Jain AK (2010) Matching forensic sketches to mug shot photos. IEEE Trans Pattern Anal Mach Intell 33(3):639\u2013646","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"8801_CR8","doi-asserted-by":"publisher","first-page":"1410","DOI":"10.1109\/TPAMI.2012.229","volume":"35","author":"BF Klare","year":"2012","unstructured":"Klare BF, Jain AK (2012) Heterogeneous face recognition using kernel prototype similarities. IEEE Trans Pattern Anal Mach Intell 35(6):1410\u20131422","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8801_CR9","doi-asserted-by":"publisher","first-page":"27135","DOI":"10.1109\/ACCESS.2019.2897599","volume":"7","author":"S Setumin","year":"2019","unstructured":"Setumin S, Suandi SA (2019) Cascaded static and dynamic local feature extractions for face sketch to photo matching. IEEE Access 7:27135\u201327145","journal-title":"IEEE Access"},{"key":"8801_CR10","doi-asserted-by":"crossref","unstructured":"Tang X, Wang X (2003) Face sketch synthesis and recognition. In: Proceedings ninth IEEE international conference on computer vision. IEEE, pp 687\u2013694","DOI":"10.1109\/ICCV.2003.1238414"},{"key":"8801_CR11","unstructured":"Liu Q, Tang X, Jin H, Lu H, Ma S (2005) A nonlinear approach for face sketch synthesis and recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition. vol.\u00a01. IEEE, pp 1005\u20131010"},{"key":"8801_CR12","doi-asserted-by":"crossref","unstructured":"Zhang L, Lin L, Wu X, Ding S, Zhang L (2015) End-to-end photo-sketch generation via fully convolutional representation learning. In: Proceedings of the 5th ACM on international conference on multimedia retrieval, pp 627\u2013634","DOI":"10.1145\/2671188.2749321"},{"key":"8801_CR13","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.patcog.2017.11.008","volume":"76","author":"N Wang","year":"2018","unstructured":"Wang N, Gao X, Li J (2018) Random sampling for fast face sketch synthesis. Pattern Recogn 76:215\u2013227","journal-title":"Pattern Recogn"},{"key":"8801_CR14","doi-asserted-by":"publisher","first-page":"154971","DOI":"10.1109\/ACCESS.2019.2949070","volume":"7","author":"J Zheng","year":"2019","unstructured":"Zheng J, Song W, Wu Y, Xu R, Liu F (2019) Feature encoder guided generative adversarial network for face photo-sketch synthesis. IEEE Access 7:154971\u2013154985","journal-title":"IEEE Access"},{"issue":"6","key":"8801_CR15","doi-asserted-by":"publisher","first-page":"1820","DOI":"10.1007\/s11263-021-01442-2","volume":"129","author":"M Zhu","year":"2021","unstructured":"Zhu M, Li J, Wang N, Gao X (2021) Learning deep patch representation for probabilistic graphical model-based face sketch synthesiss. Int J Comput Vis. 129(6):1820\u20131836","journal-title":"Int J Comput Vis"},{"key":"8801_CR16","doi-asserted-by":"crossref","unstructured":"Klare B, Jain AK (2010) Sketch-to-photo matching: a feature-based approach. In: Biometric technology for human identification VII. vol. 7667. International Society for Optics and Photonics, pp 766702","DOI":"10.1117\/12.849821"},{"key":"8801_CR17","doi-asserted-by":"crossref","unstructured":"Galoogahi HK, Sim T (2012) Face sketch recognition by local Radon binary pattern: LRBP. In: 2012 19th IEEE international conference on image processing. IEEE, pp 1837\u20131840","DOI":"10.1109\/ICME.2012.128"},{"issue":"7","key":"8801_CR18","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","volume":"24","author":"T Ojala","year":"2002","unstructured":"Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Mach Intell 24(7):971\u2013987","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8801_CR19","doi-asserted-by":"crossref","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition. vol\u00a01. IEEE, pp 886\u2013893","DOI":"10.1109\/CVPR.2005.177"},{"issue":"6","key":"8801_CR20","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1007\/s11263-018-01142-4","volume":"127","author":"Y Wen","year":"2019","unstructured":"Wen Y, Zhang K, Li Z, Qiao Y (2019) A comprehensive study on center loss for deep face recognition. Int J Comput Vis 127(6):668\u2013683","journal-title":"Int J Comput Vis"},{"key":"8801_CR21","doi-asserted-by":"crossref","unstructured":"Han C, Shan S, Kan M, Wu S, Chen X (2022) Personalized convolution for face recognition. In: International journal of computer vision, pp 1\u201319","DOI":"10.1007\/s11263-021-01536-x"},{"key":"8801_CR22","doi-asserted-by":"crossref","unstructured":"Saxena S, Verbeek J (2016) Heterogeneous face recognition with CNNs. In: European conference on computer vision. Springer, pp 483\u2013491","DOI":"10.1007\/978-3-319-49409-8_40"},{"issue":"1","key":"8801_CR23","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1109\/TIP.2017.2756450","volume":"27","author":"G Hu","year":"2017","unstructured":"Hu G, Peng X, Yang Y, Hospedales TM, Verbeek J (2017) Frankenstein: learning deep face representations using small data. IEEE Trans Image Process 27(1):293\u2013303","journal-title":"IEEE Trans Image Process"},{"key":"8801_CR24","doi-asserted-by":"crossref","unstructured":"Mittal P, Vatsa M, Singh R (2015) Composite sketch recognition via deep network-a transfer learning approach. In: 2015 international conference on biometrics (ICB). IEEE, pp 251\u2013256","DOI":"10.1109\/ICB.2015.7139092"},{"key":"8801_CR25","doi-asserted-by":"crossref","unstructured":"Fu C, Wu X, Hu Y, Huang H, He R (2021) Dvg-face: Dual variational generation for heterogeneous face recognition. In: IEEE transactions on pattern analysis and machine intelligence","DOI":"10.1109\/TPAMI.2021.3052549"},{"key":"8801_CR26","doi-asserted-by":"crossref","unstructured":"Wu X, Song L, He R, Tan T (2018) Coupled deep learning for heterogeneous face recognition. In: Proceedings of the AAAI conference on artificial intelligence, vol\u00a032","DOI":"10.1609\/aaai.v32i1.11500"},{"issue":"12","key":"8801_CR27","doi-asserted-by":"publisher","first-page":"9175","DOI":"10.1007\/s00521-019-04242-5","volume":"31","author":"W Wan","year":"2019","unstructured":"Wan W, Gao Y, Lee HJ (2019) Transfer deep feature learning for face sketch recognition. Neural Comput Appl 31(12):9175\u20139184","journal-title":"Neural Comput Appl"},{"key":"8801_CR28","unstructured":"Simard PY, Steinkraus D, Platt JC, et\u00a0al (2003) Best practices for convolutional neural networks applied to visual document analysis. In: Icdar, vol\u00a03"},{"issue":"6","key":"8801_CR29","doi-asserted-by":"publisher","first-page":"1731","DOI":"10.1109\/TNNLS.2018.2872675","volume":"30","author":"B Cao","year":"2018","unstructured":"Cao B, Wang N, Li J, Gao X (2018) Data augmentation-based joint learning for heterogeneous face recognition. IEEE Trans Neural Netw Learn Syst 30(6):1731\u20131743","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"8801_CR30","doi-asserted-by":"crossref","unstructured":"Williford JR, May BB, Byrne J (2020) Explainable face recognition. In: European conference on computer vision. Springer, pp 248\u2013263","DOI":"10.1007\/978-3-030-58621-8_15"},{"issue":"7","key":"8801_CR31","doi-asserted-by":"publisher","first-page":"2877","DOI":"10.1109\/TIP.2014.2321495","volume":"23","author":"KC Fan","year":"2014","unstructured":"Fan KC, Hung TY (2014) A novel local pattern descriptor-local vector pattern in high-order derivative space for face recognition. IEEE Trans Image Process 23(7):2877\u20132891","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"8801_CR32","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1007\/s12559-018-9593-6","volume":"11","author":"J Kim","year":"2019","unstructured":"Kim J, Oh K, Oh BS, Lin Z, Toh KA (2019) A line feature extraction method for finger-knuckle-print verification. Cogn Comput 11(1):50\u201370","journal-title":"Cogn Comput"},{"issue":"11","key":"8801_CR33","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE. 86(11):2278\u20132324","journal-title":"Proc IEEE."},{"key":"8801_CR34","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"8801_CR35","unstructured":"Tolias G, Sicre R, J\u00e9gou H (2016) Particular object retrieval with integral max-pooling of CNN activations. In: International Conference on Learning Representations, pp 1\u201312"},{"key":"8801_CR36","doi-asserted-by":"crossref","unstructured":"Pinheiro PO, Collobert R (2015) From image-level to pixel-level labeling with convolutional networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1713\u20131721","DOI":"10.1109\/CVPR.2015.7298780"},{"issue":"1","key":"8801_CR37","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/BF01584082","volume":"1","author":"J Edmonds","year":"1971","unstructured":"Edmonds J (1971) Matroids and the greedy algorithm. Math Program 1(1):127\u2013136","journal-title":"Math Program"},{"key":"8801_CR38","doi-asserted-by":"crossref","unstructured":"Zhang Y, Ti\u0148o P, Leonardis A, Tang K (2021) A survey on neural network interpretability. In: IEEE transactions on emerging topics in computational intelligence","DOI":"10.1109\/TETCI.2021.3100641"},{"key":"8801_CR39","doi-asserted-by":"crossref","unstructured":"Caruana R, Lawrence S, Giles C (2000) Overfitting in neural nets: backpropagation, conjugate gradient, and early stopping. In; Advances in neural information processing systems, vol 13","DOI":"10.1109\/IJCNN.2000.857823"},{"issue":"1","key":"8801_CR40","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/TIFS.2012.2228856","volume":"8","author":"H Han","year":"2012","unstructured":"Han H, Klare BF, Bonnen K, Jain AK (2012) Matching composite sketches to face photos: a component-based approach. IEEE Trans Inf Forensics Secur 8(1):191\u2013204","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"8801_CR41","doi-asserted-by":"crossref","unstructured":"Chan CH, Kittler J, Messer K (2007) Multi-scale local binary pattern histograms for face recognition. In: International conference on biometrics. Springer, pp 809\u2013818","DOI":"10.1007\/978-3-540-74549-5_85"},{"key":"8801_CR42","doi-asserted-by":"crossref","unstructured":"Petpon A, Srisuk S (2009) Face recognition with local line binary pattern. In: 2009 Fifth international conference on image and graphics. IEEE, pp 533\u2013539","DOI":"10.1109\/ICIG.2009.123"},{"issue":"3","key":"8801_CR43","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1109\/TPAMI.2015.2462338","volume":"38","author":"C Ding","year":"2015","unstructured":"Ding C, Choi J, Tao D, Davis LS (2015) Multi-directional multi-level dual-cross patterns for robust face recognition. IEEE Trans Pattern Anal Mach Intell 38(3):518\u2013531","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8801_CR44","doi-asserted-by":"crossref","unstructured":"Parkhi OM, Vedaldi A, Zisserman A (2015) Deep face recognition. In: Proceedings of the british machine vision conference. BMVA Press, pp 41.1\u201341.12","DOI":"10.5244\/C.29.41"},{"issue":"11","key":"8801_CR45","doi-asserted-by":"publisher","first-page":"2884","DOI":"10.1109\/TIFS.2018.2833032","volume":"13","author":"X Wu","year":"2018","unstructured":"Wu X, He R, Sun Z, Tan T (2018) A light cnn for deep face representation with noisy labels. IEEE Trans Inf Forensics Secur 13(11):2884\u20132896","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"8801_CR46","doi-asserted-by":"crossref","unstructured":"Wang H, Wang Y, Zhou Z, Ji X, Gong D, Zhou J, et\u00a0al (2018) Cosface: large margin cosine loss for deep face recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5265\u20135274","DOI":"10.1109\/CVPR.2018.00552"},{"key":"8801_CR47","doi-asserted-by":"crossref","unstructured":"Deng J, Guo J, Xue N, Zafeiriou S (2019) Arcface: Additive angular margin loss for deep face recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4690\u20134699","DOI":"10.1109\/CVPR.2019.00482"},{"key":"8801_CR48","doi-asserted-by":"crossref","unstructured":"Zeiler MD, Fergus R (2014) Visualizing and understanding convolutional networks. In: European conference on computer vision. Springer, pp 818\u2013833","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"8801_CR49","doi-asserted-by":"crossref","unstructured":"Brazdil PB, Soares C (2000) A comparison of ranking methods for classification algorithm selection. In: European conference on machine learning. Springer, pp 63\u201375","DOI":"10.1007\/3-540-45164-1_8"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08801-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08801-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08801-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T00:19:24Z","timestamp":1693354764000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08801-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,24]]},"references-count":49,"journal-issue":{"issue":"28","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["8801"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08801-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,24]]},"assertion":[{"value":"1 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 June 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}