{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T08:57:06Z","timestamp":1774601826738,"version":"3.50.1"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,9,12]],"date-time":"2020-09-12T00:00:00Z","timestamp":1599868800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,12]],"date-time":"2020-09-12T00:00:00Z","timestamp":1599868800000},"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":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s11042-020-09663-2","type":"journal-article","created":{"date-parts":[[2020,9,12]],"date-time":"2020-09-12T16:02:59Z","timestamp":1599926579000},"page":"2243-2262","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":72,"title":["A novel approach for facial expression recognition using local binary pattern with adaptive window"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3848-7152","authenticated-orcid":false,"given":"Durga Ganga Rao","family":"Kola","sequence":"first","affiliation":[]},{"given":"Srinivas Kumar","family":"Samayamantula","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,12]]},"reference":[{"issue":"12","key":"9663_CR1","doi-asserted-by":"publisher","first-page":"2037","DOI":"10.1109\/TPAMI.2006.244","volume":"28","author":"T Ahonen","year":"2006","unstructured":"Ahonen T, Hadid A, Pietikainen M (2006) Face description with local binary patterns: application to face recognition. IEEE Trans Pattern Anal Mach Intell 28(12):2037\u20132041","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9663_CR2","doi-asserted-by":"crossref","unstructured":"An Q, Han Y, Li J, Lu S (2018) Human-computer interaction nursing system and related algorithms for severely paralyzed patients. In: 2018 15th International conference on control, automation, robotics and vision (ICARCV). IEEE, pp 1929\u20131935","DOI":"10.1109\/ICARCV.2018.8581104"},{"key":"9663_CR3","doi-asserted-by":"crossref","unstructured":"Aneja D, Colburn A, Faigin G, Shapiro L, Mones B (2016) Modeling stylized character expressions via deep learning. In: Asian conference on computer vision. Springer, pp 136\u2013153","DOI":"10.1007\/978-3-319-54184-6_9"},{"key":"9663_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-28854-3","volume-title":"Image feature detectors and descriptors","author":"AI Awad","year":"2016","unstructured":"Awad AI, Hassaballah M (2016) Image feature detectors and descriptors. Studies in Computational Intelligence Springer International Publishing, Cham"},{"issue":"7","key":"9663_CR5","doi-asserted-by":"publisher","first-page":"1056","DOI":"10.1016\/j.engappai.2007.11.010","volume":"21","author":"S Bashyal","year":"2008","unstructured":"Bashyal S, Venayagamoorthy GK (2008) Recognition of facial expressions using gabor wavelets and learning vector quantization. Eng Appl Artif Intell 21 (7):1056\u20131064","journal-title":"Eng Appl Artif Intell"},{"key":"9663_CR6","doi-asserted-by":"crossref","unstructured":"Bellamkonda S, Gopalan N (2018) Facial expression recognition using kirsch edge detection, lbp and gabor wavelets. In: 2018 Second international conference on intelligent computing and control systems (ICICCS). IEEE, pp 1457\u20131461","DOI":"10.1109\/ICCONS.2018.8662971"},{"key":"9663_CR7","doi-asserted-by":"crossref","unstructured":"Bi H, Li N, Guan H, Lu D, Yang L (2019) A multi-scale conditional generative adversarial network for face sketch synthesis. In: 2019 IEEE international conference on image processing (ICIP). IEEE, pp 3876\u20133880","DOI":"10.1109\/ICIP.2019.8803629"},{"key":"9663_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.sigpro.2015.04.007","volume":"117","author":"WL Chao","year":"2015","unstructured":"Chao WL, Ding JJ, Liu JZ (2015) Facial expression recognition based on improved local binary pattern and class-regularized locality preserving projection. Signal Process 117:1\u201310","journal-title":"Signal Process"},{"key":"9663_CR9","doi-asserted-by":"publisher","first-page":"49741","DOI":"10.1109\/ACCESS.2020.2980060","volume":"8","author":"A Chen","year":"2020","unstructured":"Chen A, Xing H, Wang F (2020) A facial expression recognition method using deep convolutional neural networks based on edge computing. IEEE Access 8:49741\u201349751","journal-title":"IEEE Access"},{"key":"9663_CR10","doi-asserted-by":"crossref","unstructured":"Chengeta K, Viriri S (2019) A review of local, holistic and deep learning approaches in facial expressions recognition. In: 2019 Conference on information communications technology and society (ICTAS). IEEE, pp 1\u20137","DOI":"10.1109\/ICTAS.2019.8703521"},{"key":"9663_CR11","doi-asserted-by":"crossref","unstructured":"Cho M, Kim T, Kim IJ, Lee S (2020) Relational deep feature learning for heterogeneous face recognition. arXiv:200300697","DOI":"10.1109\/TIFS.2020.3013186"},{"issue":"3","key":"9663_CR12","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273\u2013297","journal-title":"Mach Learn"},{"issue":"20","key":"9663_CR13","doi-asserted-by":"publisher","first-page":"6320","DOI":"10.1016\/j.ijleo.2014.08.003","volume":"125","author":"Z Dan","year":"2014","unstructured":"Dan Z, Chen Y, Yang Z, Wu G (2014) An improved local binary pattern for texture classification. Optik 125(20):6320\u20136324","journal-title":"Optik"},{"issue":"10","key":"9663_CR14","doi-asserted-by":"publisher","first-page":"974","DOI":"10.1109\/34.799905","volume":"21","author":"G Donato","year":"1999","unstructured":"Donato G, Bartlett MS, Hager JC, Ekman P, Sejnowski TJ (1999) Classifying facial actions. IEEE Trans Pattern Anal Mach Intell 21(10):974\u2013989","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9663_CR15","doi-asserted-by":"crossref","unstructured":"Ekweariri AN, Yurtkan K (2017) Facial expression recognition using enhanced local binary patterns. In: 2017 9th International conference on computational intelligence and communication networks (CICN). IEEE, pp 43\u201347","DOI":"10.1109\/CICN.2017.8319353"},{"key":"9663_CR16","doi-asserted-by":"crossref","unstructured":"Eng S, Ali H, Cheah A, Chong Y (2019) Facial expression recognition in jaffe and kdef datasets using histogram of oriented gradients and support vector machine. In: IOP Conference series: materials science and engineering, vol 705. IOP Publishing, p 012031","DOI":"10.1088\/1757-899X\/705\/1\/012031"},{"key":"9663_CR17","doi-asserted-by":"crossref","unstructured":"Fan DP, Cheng MM, Liu JJ, Gao SH, Hou Q, Borji A (2018) Salient objects in clutter: Bringing salient object detection to the foreground. In: Proceedings of the European conference on computer vision (ECCV), pp 186\u2013202","DOI":"10.1007\/978-3-030-01267-0_12"},{"key":"9663_CR18","doi-asserted-by":"crossref","unstructured":"Fan DP, Zhang S, Wu YH, Liu Y, Cheng MM, Ren B, Rosin PL, Ji R (2019) Scoot: A perceptual metric for facial sketches. In: Proceedings of the IEEE international conference on computer vision, pp 5612\u20135622","DOI":"10.1109\/ICCV.2019.00571"},{"key":"9663_CR19","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1016\/j.ins.2018.05.057","volume":"460","author":"N Farajzadeh","year":"2018","unstructured":"Farajzadeh N, Hashemzadeh M (2018) Exemplar-based facial expression recognition. Inf Sci 460:318\u2013330","journal-title":"Inf Sci"},{"key":"9663_CR20","doi-asserted-by":"crossref","unstructured":"Hassaballah M, Awad AI (2016) Detection and description of image features: an introduction. In: Image feature detectors and descriptors. Springer, pp 1\u20138","DOI":"10.1007\/978-3-319-28854-3_1"},{"issue":"1","key":"9663_CR21","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1186\/s13640-017-0190-5","volume":"2017","author":"RP Holder","year":"2017","unstructured":"Holder RP, Tapamo JR (2017) Improved gradient local ternary patterns for facial expression recognition. EURASIP J Image Vide Process 2017(1):42","journal-title":"EURASIP J Image Vide Process"},{"issue":"6","key":"9663_CR22","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1109\/TSMCC.2011.2118750","volume":"41","author":"D Huang","year":"2011","unstructured":"Huang D, Shan C, Ardabilian M, Wang Y, Chen L (2011) Local binary patterns and its application to facial image analysis: a survey. IEEE Trans Syst Man Cybern Part C App Rev 41(6):765\u2013781","journal-title":"IEEE Trans Syst Man Cybern Part C App Rev"},{"key":"9663_CR23","doi-asserted-by":"crossref","unstructured":"Huang Z, Song G, Zhao Y, Han J, Zhao X (2018) Smile recognition based on support vector machine and local binary pattern. In: 2018 IEEE 8th Annual international conference on cyber technology in automation, control, and intelligent systems (CYBER). IEEE, pp 938\u2013942","DOI":"10.1109\/CYBER.2018.8688313"},{"key":"9663_CR24","doi-asserted-by":"crossref","unstructured":"Huang Y, Wang Y, Tai Y, Liu X, Shen P, Li S, Li J, Huang F (2020) Curricularface: adaptive curriculum learning loss for deep face recognition. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5901\u20135910","DOI":"10.1109\/CVPR42600.2020.00594"},{"key":"9663_CR25","doi-asserted-by":"crossref","unstructured":"Jabid T, Kabir MH, Chae O (2010) Local directional pattern (ldp) for face recognition. In: 2010 Digest of technical papers international conference on consumer electronics (ICCE). IEEE, pp 329\u2013330","DOI":"10.1109\/ICCE.2010.5418801"},{"issue":"5","key":"9663_CR26","doi-asserted-by":"publisher","first-page":"784","DOI":"10.4218\/etrij.10.1510.0132","volume":"32","author":"T Jabid","year":"2010","unstructured":"Jabid T, Kabir MH, Chae O (2010) Robust facial expression recognition based on local directional pattern. ETRI J 32(5):784\u2013794","journal-title":"ETRI J"},{"key":"9663_CR27","doi-asserted-by":"crossref","unstructured":"Jaiswal S, Nandi G (2019) Robust real-time emotion detection system using cnn architecture. Neural Comput & Applic, 1\u201310","DOI":"10.1007\/s00521-019-04564-4"},{"key":"9663_CR28","doi-asserted-by":"crossref","unstructured":"Jung H, Lee S, Park S, Kim B, Kim J, Lee I, Ahn C (2015) Development of deep learning-based facial expression recognition system. In: 2015 21st Korea-Japan joint workshop on frontiers of computer vision (FCV). IEEE, pp 1\u20134","DOI":"10.1109\/FCV.2015.7103729"},{"key":"9663_CR29","doi-asserted-by":"crossref","unstructured":"Kanade T, Cohn JF, Tian Y (2000) Comprehensive database for facial expression analysis. In: Proceedings Fourth IEEE international conference on automatic face and gesture recognition (Cat. No. PR00580). IEEE, pp 46\u201353","DOI":"10.1109\/AFGR.2000.840611"},{"key":"9663_CR30","doi-asserted-by":"publisher","first-page":"106019","DOI":"10.1016\/j.asoc.2019.106019","volume":"87","author":"K Kaplan","year":"2020","unstructured":"Kaplan K, Kaya Y, Kuncan M, Minaz MR, Ertun\u00e7 HM (2020) An improved feature extraction method using texture analysis with lbp for bearing fault diagnosis. Appl Soft Comput 87:106019","journal-title":"Appl Soft Comput"},{"key":"9663_CR31","doi-asserted-by":"crossref","unstructured":"Kaushik MS, Kandali AB (2017) Recognition of facial expressions extracting salient features using local binary patterns and histogram of oriented gradients. In: 2017 International conference on energy, communication, data analytics and soft computing (ICECDS). IEEE, pp 1201\u20131205","DOI":"10.1109\/ICECDS.2017.8389632"},{"issue":"10","key":"9663_CR32","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1016\/j.patrec.2013.03.022","volume":"34","author":"RA Khan","year":"2013","unstructured":"Khan RA, Meyer A, Konik H, Bouakaz S (2013) Framework for reliable, real-time facial expression recognition for low resolution images. Pattern Recogn Lett 34(10):1159\u20131168","journal-title":"Pattern Recogn Lett"},{"key":"9663_CR33","doi-asserted-by":"publisher","first-page":"41273","DOI":"10.1109\/ACCESS.2019.2907327","volume":"7","author":"JH Kim","year":"2019","unstructured":"Kim JH, Kim BG, Roy PP, Jeong DM (2019) Efficient facial expression recognition algorithm based on hierarchical deep neural network structure. IEEE Access 7:41273\u201341285","journal-title":"IEEE Access"},{"key":"9663_CR34","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.image.2017.08.001","volume":"58","author":"K Lekdioui","year":"2017","unstructured":"Lekdioui K, Messoussi R, Ruichek Y, Chaabi Y, Touahni R (2017) Facial decomposition for expression recognition using texture\/shape descriptors and svm classifier. Signal Process Image Commun 58:300\u2013312","journal-title":"Signal Process Image Commun"},{"key":"9663_CR35","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.procs.2017.03.069","volume":"107","author":"J Li","year":"2017","unstructured":"Li J, Zhang D, Zhang J, Zhang J, Li T, Xia Y, Yan Q, Xun L (2017) Facial expression recognition with faster r-cnn. Procedia Comput Sci 107:135\u2013140","journal-title":"Procedia Comput Sci"},{"key":"9663_CR36","doi-asserted-by":"crossref","unstructured":"Liliana D (2019) Emotion recognition from facial expression using deep convolutional neural network. In: Journal of physics: conference series, vol 1193. IOP Publishing, p 012004","DOI":"10.1088\/1742-6596\/1193\/1\/012004"},{"key":"9663_CR37","doi-asserted-by":"crossref","unstructured":"Lyons M, Akamatsu S, Kamachi M, Gyoba J (1998) Coding facial expressions with gabor wavelets. In: Proceedings Third IEEE international conference on automatic face and gesture recognition. IEEE, pp 200\u2013205","DOI":"10.1109\/AFGR.1998.670949"},{"key":"9663_CR38","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.patrec.2015.11.019","volume":"71","author":"R Mehta","year":"2016","unstructured":"Mehta R, Egiazarian K (2016) Dominant rotated local binary patterns (drlbp) for texture classification. Pattern Recogn Lett 71:16\u201322","journal-title":"Pattern Recogn Lett"},{"key":"9663_CR39","unstructured":"Minaee S, Abdolrashidi A (2019) Deep-emotion: Facial expression recognition using attentional convolutional network. arXiv:1902.01019"},{"issue":"21","key":"9663_CR40","doi-asserted-by":"publisher","first-page":"28725","DOI":"10.1007\/s11042-018-6040-3","volume":"77","author":"S Nigam","year":"2018","unstructured":"Nigam S, Singh R, Misra A (2018) Efficient facial expression recognition using histogram of oriented gradients in wavelet domain. Multimed Tools Appl 77(21):28725\u201328747","journal-title":"Multimed Tools Appl"},{"issue":"7","key":"9663_CR41","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"},{"issue":"6","key":"9663_CR42","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1109\/LSP.2017.2694460","volume":"24","author":"Z Pan","year":"2017","unstructured":"Pan Z, Wu X, Li Z, Zhou Z (2017) Local adaptive binary patterns using diamond sampling structure for texture classification. IEEE Signal Process Lett 24(6):828\u2013832","journal-title":"IEEE Signal Process Lett"},{"key":"9663_CR43","doi-asserted-by":"crossref","unstructured":"Patil M, Veni S (2019) Driver emotion recognition for enhancement of human machine interface in vehicles. In: 2019 International conference on communication and signal processing (ICCSP). IEEE, pp 0420\u20130424","DOI":"10.1109\/ICCSP.2019.8698045"},{"key":"9663_CR44","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.eswa.2016.08.047","volume":"66","author":"LA Perez-Gaspar","year":"2016","unstructured":"Perez-Gaspar LA, Caballero-Morales SO, Trujillo-Romero F (2016) Multimodal emotion recognition with evolutionary computation for human-robot interaction. Expert Syst Appl 66:42\u201361","journal-title":"Expert Syst Appl"},{"key":"9663_CR45","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1016\/j.procs.2017.10.038","volume":"116","author":"DA Pitaloka","year":"2017","unstructured":"Pitaloka DA, Wulandari A, Basaruddin T, Liliana DY (2017) Enhancing cnn with preprocessing stage in automatic emotion recognition. Procedia Comput Sci 116:523\u2013529","journal-title":"Procedia Comput Sci"},{"key":"9663_CR46","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.procs.2016.04.072","volume":"84","author":"SD Roy","year":"2016","unstructured":"Roy SD, Bhowmik MK, Saha P, Ghosh A K (2016) An approach for automatic pain detection through facial expression. Procedia Comput Sci 84:99\u2013106","journal-title":"Procedia Comput Sci"},{"key":"9663_CR47","doi-asserted-by":"crossref","unstructured":"Salahat E, Qasaimeh M (2017) Recent advances in features extraction and description algorithms: a comprehensive survey. In: 2017 IEEE international conference on industrial technology (ICIT). IEEE, pp 1059\u20131063","DOI":"10.1109\/ICIT.2017.7915508"},{"key":"9663_CR48","unstructured":"Shan C, Gong S, McOwan PW (2005) Robust facial expression recognition using local binary patterns. In: IEEE International conference on image processing 2005, vol 2. IEEE, pp II\u2013370"},{"issue":"6","key":"9663_CR49","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1016\/j.imavis.2008.08.005","volume":"27","author":"C Shan","year":"2009","unstructured":"Shan C, Gong S, McOwan PW (2009) Facial expression recognition based on local binary patterns: a comprehensive study. Image Vision Comput 27 (6):803\u2013816","journal-title":"Image Vision Comput"},{"key":"9663_CR50","doi-asserted-by":"crossref","unstructured":"Shan K, Guo J, You W, Lu D, Bie R (2017) Automatic facial expression recognition based on a deep convolutional-neural-network structure. In: 2017 IEEE 15th international conference on software engineering research, management and applications (SERA). IEEE, pp 123\u2013128","DOI":"10.1109\/SERA.2017.7965717"},{"issue":"6","key":"9663_CR51","doi-asserted-by":"publisher","first-page":"1635","DOI":"10.1109\/TIP.2010.2042645","volume":"19","author":"X Tan","year":"2010","unstructured":"Tan X, Triggs B (2010) Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans Image Process 19(6):1635\u20131650","journal-title":"IEEE Trans Image Process"},{"issue":"6","key":"9663_CR52","doi-asserted-by":"publisher","first-page":"902","DOI":"10.1016\/j.imavis.2009.11.005","volume":"28","author":"CE Thomaz","year":"2010","unstructured":"Thomaz CE, Giraldi GA (2010) A new ranking method for principal components analysis and its application to face image analysis. Image Vision Comput 28(6):902\u2013913","journal-title":"Image Vision Comput"},{"issue":"16","key":"9663_CR53","doi-asserted-by":"publisher","first-page":"4186","DOI":"10.1016\/j.ijleo.2014.04.062","volume":"125","author":"Y Tong","year":"2014","unstructured":"Tong Y, Chen R, Cheng Y (2014) Facial expression recognition algorithm using lgc based on horizontal and diagonal prior principle. Optik 125 (16):4186\u20134189","journal-title":"Optik"},{"key":"9663_CR54","doi-asserted-by":"publisher","first-page":"4630","DOI":"10.1109\/ACCESS.2017.2784096","volume":"6","author":"B Yang","year":"2017","unstructured":"Yang B, Cao J, Ni R, Zhang Y (2017) Facial expression recognition using weighted mixture deep neural network based on double-channel facial images. IEEE Access 6:4630\u20134640","journal-title":"IEEE Access"},{"key":"9663_CR55","doi-asserted-by":"crossref","unstructured":"Yee SY, Rassem TH, Mohammed MF, Makbol NM (2019) Performance evaluation of completed local ternary pattern (cltp) for face image recognition. Perform Eval, 10(4)","DOI":"10.14569\/IJACSA.2019.0100446"},{"key":"9663_CR56","doi-asserted-by":"crossref","unstructured":"Zhang J, Fan DP, Dai Y, Anwar S, Saleh FS, Zhang T, Barnes N (2020) Uc-net: uncertainty inspired rgb-d saliency detection via conditional variational autoencoders. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8582\u20138591","DOI":"10.1109\/CVPR42600.2020.00861"},{"issue":"23","key":"9663_CR57","doi-asserted-by":"publisher","first-page":"4501","DOI":"10.1016\/j.ijleo.2015.08.185","volume":"126","author":"Y Zhang","year":"2015","unstructured":"Zhang Y, Hua C (2015) Driver fatigue recognition based on facial expression analysis using local binary patterns. Optik 126(23):4501\u20134505","journal-title":"Optik"},{"key":"9663_CR58","doi-asserted-by":"crossref","unstructured":"Zhang J, Yu X, Li A, Song P, Liu B, Dai Y (2020) Weakly-supervised salient object detection via scribble annotations. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12546\u201312555","DOI":"10.1109\/CVPR42600.2020.01256"},{"key":"9663_CR59","doi-asserted-by":"crossref","unstructured":"Zhao JX, Liu JJ, Fan DP, Cao Y, Yang J, Cheng MM (2019) Egnet: Edge guidance network for salient object detection. In: Proceedings of the IEEE international conference on computer vision, pp 8779\u20138788","DOI":"10.1109\/ICCV.2019.00887"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09663-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09663-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09663-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,11]],"date-time":"2021-09-11T23:25:33Z","timestamp":1631402733000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09663-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,12]]},"references-count":59,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["9663"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09663-2","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,12]]},"assertion":[{"value":"13 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 July 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 August 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 September 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with Ethical Standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of interests"}}]}}