{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T22:32:19Z","timestamp":1767652339720,"version":"3.37.3"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2021,3,10]],"date-time":"2021-03-10T00:00:00Z","timestamp":1615334400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,3,10]],"date-time":"2021-03-10T00:00:00Z","timestamp":1615334400000},"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":[[2021,6]]},"DOI":"10.1007\/s11042-021-10703-8","type":"journal-article","created":{"date-parts":[[2021,3,10]],"date-time":"2021-03-10T01:02:41Z","timestamp":1615338161000},"page":"20849-20867","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Deep learning based robust forward collision warning system with range prediction"],"prefix":"10.1007","volume":"80","author":[{"given":"N.","family":"Venkateswaran","sequence":"first","affiliation":[]},{"given":"W. Jino","family":"Hans","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0793-9251","authenticated-orcid":false,"given":"N.","family":"Padmapriya","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,10]]},"reference":[{"key":"10703_CR1","doi-asserted-by":"crossref","unstructured":"Adamshuk R, Carvalho D, Jo\u00e3o HZ, Neme E, Margraf S, Okida A, Tusset MM, Santos, et al. (2017) On the applicability of inverse perspective mapping for the forward distance estimation based on the HSV colormap. In: 2017 IEEE International Conference on Industrial Technology (ICIT), pp 1036\u20131041","DOI":"10.1109\/ICIT.2017.7915504"},{"issue":"8","key":"10703_CR2","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/s0262-8856(97)00093-0","volume":"16","author":"M Bertozz","year":"1998","unstructured":"Bertozz M, Broggi A, Fascioli A et al (1998) Stereo inverse perspec- tive mapping: theory and applications. Image Vis Comput 16(8):585\u2013590. https:\/\/doi.org\/10.1016\/s0262-8856(97)00093-0","journal-title":"Image Vis Comput"},{"issue":"12","key":"10703_CR3","doi-asserted-by":"publisher","first-page":"5497","DOI":"10.1109\/tip.2014.2364919","volume":"23","author":"Z Cai","year":"2014","unstructured":"Cai Z, Wen L, Lei Z, Vasconcelos N, Li SZ (2014) Robust deformable and occluded object tracking with dynamic graph. IEEE Trans Image Process 23(12):5497\u20135509. https:\/\/doi.org\/10.1109\/tip.2014.2364919","journal-title":"IEEE Trans Image Process"},{"key":"10703_CR4","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1109\/tip.2016.2520370","volume":"25","author":"L Cehovin","year":"2016","unstructured":"Cehovin L, Leonardis A, Kristan M (2016) Visual object tracking performance measures revisited. IEEE Trans Image Process 25:1261\u20131274. https:\/\/doi.org\/10.1109\/tip.2016.2520370","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"10703_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1049\/iet-its.2011.0019","volume":"6","author":"YM Chan","year":"2012","unstructured":"Chan YM, Huang SS, Fu LC, Hsiao PY, Lo MF (2012) Vehicle detection and tracking under various lighting conditions using a particle filter. IET Intell Transp Syst 6(1):1\u20138. https:\/\/doi.org\/10.1049\/iet-its.2011.0019","journal-title":"IET Intell Transp Syst"},{"key":"10703_CR6","doi-asserted-by":"publisher","first-page":"19959","DOI":"10.1109\/access.2018.2815149","volume":"6","author":"J Chu","year":"2018","unstructured":"Chu J, Guo Z, Leng L et al (2018) Object detection based on multi-layer convolution feature fusion and online hard example mining. IEEE Access 6:19959\u201319967. https:\/\/doi.org\/10.1109\/access.2018.2815149","journal-title":"IEEE Access"},{"key":"10703_CR7","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1109\/access.2019.2961778","volume":"8","author":"J Chu","year":"2020","unstructured":"Chu J, Tu X, Leng L, Miao J et al (2020a) Double-channel object tracking with position deviation suppression. IEEE Access 8:856\u2013866. https:\/\/doi.org\/10.1109\/access.2019.2961778","journal-title":"IEEE Access"},{"key":"10703_CR8","doi-asserted-by":"publisher","first-page":"114705","DOI":"10.1109\/access.2020.3003917","volume":"8","author":"J Chu","year":"2020","unstructured":"Chu J, Zhang Y, Li S, Leng L, Miao J et al (2020b) Syncretic-NMS: a merging non-maximum suppression algorithm for instance segmentation. IEEE Access 8:114705\u2013114714. https:\/\/doi.org\/10.1109\/access.2020.3003917","journal-title":"IEEE Access"},{"key":"10703_CR9","first-page":"1090","volume-title":"Adaptive color attributes for real-time visual tracking","author":"F Danelljan","year":"2014","unstructured":"Danelljan F, Khan M, Felsberg J, Deweijer V (2014) Adaptive color attributes for real-time visual tracking. CVPR, In, pp 1090\u20131097"},{"issue":"8","key":"10703_CR10","doi-asserted-by":"publisher","first-page":"3536","DOI":"10.1109\/TITS.2019.2931297","volume":"21","author":"A Dhiman","year":"2020","unstructured":"Dhiman A, Klette R (2020) Pothole detection using computer vision and learning. IEEE Trans Intell Transp Syst 21(8):3536\u20133550. https:\/\/doi.org\/10.1109\/TITS.2019.2931297","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"10703_CR11","unstructured":"GitHub (2019) Kalman filter multi object tracking. URL https:\/\/github.com\/srianant\/kalman_filter_multi_object_tracking.git"},{"issue":"5","key":"10703_CR12","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1109\/76.718504","volume":"8","author":"C Gu","year":"1998","unstructured":"Gu C, Lee MC (1998) Semiautomatic segmentation and tracking of semantic video objects. IEEE Trans Circuits Syst Video Tech-nol 8(5):572\u2013584. https:\/\/doi.org\/10.1109\/76.718504","journal-title":"IEEE Trans Circuits Syst Video Tech-nol"},{"key":"10703_CR13","doi-asserted-by":"crossref","unstructured":"Guo Q, Feng W, Zhou C, Huang R, Wan L, Wang S (2017a) Learning dynamic siamese network for visual object tracking. Proc ICCV pp:1763\u20131771","DOI":"10.1109\/ICCV.2017.196"},{"issue":"12","key":"10703_CR14","doi-asserted-by":"publisher","first-page":"5692","DOI":"10.1109\/tip.2017.2745205","volume":"26","author":"Q Guo","year":"2017","unstructured":"Guo Q, Feng W, Zhou C, Pun CM, Wu B (2017b) Structure-regularized com- pressive tracking with online data-driven sampling. IEEE Trans Image Process 26(12):5692\u20135705. https:\/\/doi.org\/10.1109\/tip.2017.2745205","journal-title":"IEEE Trans Image Process"},{"key":"10703_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2014\/196415","volume":"2014","author":"J Hariyono","year":"2014","unstructured":"Hariyono J, Hoang VD, Jo KH (2014) Moving object localization using optical flow for pedestrian detection from a moving vehicle. Sci World J 2014:1\u20138. https:\/\/doi.org\/10.1155\/2014\/196415","journal-title":"Sci World J"},{"volume-title":"Deep learning in computer vision principles and applications","year":"2020","key":"10703_CR16","unstructured":"Hassaballah M, Awad AI (eds) (2020) Deep learning in computer vision principles and applications. CRC Press, Digital Imaging and Computer Vision Series"},{"issue":"4","key":"10703_CR17","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.1007\/s10044-020-00874-9","volume":"23","author":"M Hassaballah","year":"2020","unstructured":"Hassaballah M, Kenk MA, El-Henawy IM (2020a) Local binary pattern- based on-road vehicle detection in urban traffic scene. Pattern Anal Applic 23(4):1505\u20131521. https:\/\/doi.org\/10.1007\/s10044-020-00874-9","journal-title":"Pattern Anal Applic"},{"key":"10703_CR18","doi-asserted-by":"publisher","unstructured":"Hassaballah M, Kenk MA, Muhammad K, Minaee S (2020b) Vehicle detection and tracking in adverse weather using a deep learning framework. IEEE Trans Intell Trans Syst:1\u201313. https:\/\/doi.org\/10.1109\/tits.2020.3014013","DOI":"10.1109\/tits.2020.3014013"},{"key":"10703_CR19","doi-asserted-by":"publisher","unstructured":"He K, Gkioxari G, Doll\u00e1r P, Girshick R et al (2017) Mask R-CNN. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp 2980\u20132988. https:\/\/doi.org\/10.1109\/ICCV.2017.322","DOI":"10.1109\/ICCV.2017.322"},{"key":"#cr-split#-10703_CR20.1","doi-asserted-by":"crossref","unstructured":"Huang L Z and Huang, Gong Y, Huang C, Wang X, et al. (2019) Mask scoring R-CNN. In: and others","DOI":"10.1109\/CVPR.2019.00657"},{"key":"#cr-split#-10703_CR20.2","unstructured":"(ed) 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), arXiv 2019, pp 6402-6411, URL arXiv:1903.00241"},{"issue":"6","key":"10703_CR21","doi-asserted-by":"publisher","first-page":"771","DOI":"10.7763\/ijcee.2011.v3.418","volume":"3","author":"O Ibrahim","year":"2011","unstructured":"Ibrahim O, ElGendy H, ElShafee AM (2011) Speed detection camera system using image processing techniques on video streams. Int J Comput Electric Eng 3(6):771\u2013778. https:\/\/doi.org\/10.7763\/ijcee.2011.v3.418","journal-title":"Int J Comput Electric Eng"},{"key":"10703_CR22","doi-asserted-by":"publisher","first-page":"1044","DOI":"10.1007\/978-3-642-03767-2_127","volume":"5702","author":"R Jiang","year":"2009","unstructured":"Jiang R, Klette R, Vaudrey T, Wang S et al (2009) New lane model and distance transform for lane detection and tracking. Proc Comput Anal Images Patterns 5702:1044\u20131052","journal-title":"Proc Comput Anal Images Patterns"},{"issue":"4","key":"10703_CR23","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1109\/tci.2016.2600480","volume":"2","author":"H Kaur","year":"2016","unstructured":"Kaur H, Sahambi JS et al (2016) Vehicle tracking in video using fractional feedback Kalman filter. IEEE Transactions on Computational Imaging 2(4):550\u2013561. https:\/\/doi.org\/10.1109\/tci.2016.2600480","journal-title":"IEEE Transactions on Computational Imaging"},{"issue":"1","key":"10703_CR24","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1109\/tits.2007.908582","volume":"9","author":"Z Kim","year":"2008","unstructured":"Kim Z et al (2008) Robust lane detection and tracking in challenging Sce- narios. IEEE Trans Intell Trans Syst 9(1):16\u201326. https:\/\/doi.org\/10.1109\/tits.2007.908582","journal-title":"IEEE Trans Intell Trans Syst"},{"key":"10703_CR25","first-page":"3105","volume":"4","author":"N Li","year":"2004","unstructured":"Li N, Zheng (2004) Adaptive target color model updating for visual tracking using particle filter. In: 2004 IEEE international conference on systems. Man and Cybernetics, IEEE, vol 4:3105\u20133109","journal-title":"Man and Cybernetics, IEEE, vol"},{"key":"10703_CR26","doi-asserted-by":"publisher","first-page":"122772","DOI":"10.1109\/access.2020.3007261","volume":"8","author":"S Li","year":"2020","unstructured":"Li S, Chu J, Zhong G, Leng L, Miao J et al (2020) Robust visual tracking with occlusion judgment and re-detection. IEEE Access 8:122772\u2013122781. https:\/\/doi.org\/10.1109\/access.2020.3007261","journal-title":"IEEE Access"},{"issue":"4","key":"10703_CR27","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1049\/iet-its.2014.0088","volume":"9","author":"P Liu","year":"2015","unstructured":"Liu P, Li W, Wang Y, Ni H et al (2015) On-road multi-vehicle tracking algorithm based on an improved particle filter. IET Intell Transp Syst 9(4):429\u2013441","journal-title":"IET Intell Transp Syst"},{"issue":"4","key":"10703_CR28","doi-asserted-by":"publisher","first-page":"937","DOI":"10.1109\/TITS.2016.2597299","volume":"18","author":"LC Liu","year":"2017","unstructured":"Liu LC, Fang CY, Chen SW et al (2017) A novel distance estimation method leading a forward collision avoidance assist system for vehicles on highways. IEEE Trans Intell Transp Syst 18(4):937\u2013949","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"2","key":"10703_CR29","doi-asserted-by":"publisher","first-page":"1447","DOI":"10.1007\/s11071-019-05170-8","volume":"98","author":"P Liu","year":"2019","unstructured":"Liu P, Yu H, Cang S (2019) Adaptive neural network tracking control for underactuated systems with matched and mismatched disturbances. Non- linear Dynamics 98(2):1447\u20131464. https:\/\/doi.org\/10.1007\/s11071-019-05170-8","journal-title":"Non- linear Dynamics"},{"issue":"11","key":"10703_CR30","doi-asserted-by":"publisher","first-page":"2259","DOI":"10.1109\/TPAMI.2011.66","volume":"33","author":"X Mei","year":"2011","unstructured":"Mei X, Ling H (2011) Robust visual tracking and vehicle classification via sparse representation. IEEE Trans Pattern Anal Mach Intell 33(11):2259\u20132272","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10703_CR31","unstructured":"Nam H, Baek M, Han B, et al. (2016) Modeling and propagating CNNs in a tree structure for visual tracking. DOI arXiv:1608.07242, URL https:\/\/arxiv.org\/abs\/1608.07242"},{"issue":"2","key":"10703_CR32","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1109\/tits.2012.2187894","volume":"13","author":"HT Niknejad","year":"2012","unstructured":"Niknejad HT, Takeuchi A, Mita S, McAllester D (2012) On-road multivehicle tracking using deformable object model and particle filter with improved likelihood estimation. IEEE Trans Intell Transp Syst 13(2):748\u2013758. https:\/\/doi.org\/10.1109\/tits.2012.2187894","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"4","key":"10703_CR33","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1080\/18756891.2008.9727627","volume":"1","author":"A Rahman","year":"2008","unstructured":"Rahman A, Salam A, Islam M, Parthasarke, et al. (2008) An image based approach to compute object distance. Int J Comput Intell Syst 1(4):304\u2013312","journal-title":"Int J Comput Intell Syst"},{"key":"10703_CR34","doi-asserted-by":"publisher","first-page":"24023","DOI":"10.1109\/ACCESS.2017.2770178","volume":"5","author":"J Redmon","year":"2017","unstructured":"Redmon J, Divvala S, Girshick R, Farhad A et al (2017) You only look once: unified, real-time object detection. IEEE Access 5:24023\u201324031","journal-title":"IEEE Access"},{"issue":"5","key":"10703_CR35","doi-asserted-by":"publisher","first-page":"2723","DOI":"10.1109\/tits.2015.2421482","volume":"16","author":"M Rezaei","year":"2015","unstructured":"Rezaei M, Terauchi M, Klette R et al (2015) Robust vehicle detection and distance estimation under challenging lighting conditions. IEEE Trans Intell Trans Syst 16(5):2723\u20132743. https:\/\/doi.org\/10.1109\/tits.2015.2421482","journal-title":"IEEE Trans Intell Trans Syst"},{"key":"10703_CR36","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1109\/ACCESS.2016.2642981","volume":"5","author":"SU Sharma","year":"2017","unstructured":"Sharma SU, Shah DJ et al (2017) A practical animal detection and collision avoidance system using computer vision technique. IEEE Access 5:347\u2013358","journal-title":"IEEE Access"},{"issue":"2","key":"10703_CR37","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1109\/tits.2010.2040177","volume":"11","author":"S Sivaraman","year":"2010","unstructured":"Sivaraman S, Trivedi MM (2010) A general active-learning framework for on-road vehicle recognition and tracking. IEEE Trans Intell Transp Syst 11(2):267\u2013276. https:\/\/doi.org\/10.1109\/tits.2010.2040177","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"2","key":"10703_CR38","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1109\/tits.2013.2246835","volume":"14","author":"S Sivaraman","year":"2013","unstructured":"Sivaraman S, Trivedi MM (2013) Integrated lane and vehicle detection, localization, and tracking: a synergistic approach. IEEE Trans Intell Transp Syst 14(2):906\u2013917. https:\/\/doi.org\/10.1109\/tits.2013.2246835","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"9","key":"10703_CR39","doi-asserted-by":"publisher","first-page":"3487","DOI":"10.1109\/jsen.2018.2888815","volume":"19","author":"L Sun","year":"2019","unstructured":"Sun L, Zhao C, Yan Z, Liu P, Duckett T, Stolkin R (2019) A novel weakly- supervised approach for RGB-D-based nuclear waste object detection. IEEE Sensors J 19(9):3487\u20133500. https:\/\/doi.org\/10.1109\/jsen.2018.2888815","journal-title":"IEEE Sensors J"},{"key":"10703_CR40","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.1631\/FITEE.1800083","volume":"20","author":"Z Tang","year":"2019","unstructured":"Tang Z, Li C, Wu J, Liu P, Cheng S (2019a) Classification of EEG-based single-trial motor imagery tasks using a B- CSP method for BCI. Frontiers Inf Technol Electronic Eng 20:1087\u20131098. https:\/\/doi.org\/10.1631\/FITEE.1800083","journal-title":"Frontiers Inf Technol Electronic Eng"},{"key":"10703_CR41","doi-asserted-by":"publisher","first-page":"128185","DOI":"10.1109\/ACCESS.2019.2940034","volume":"7","author":"Z Tang","year":"2019","unstructured":"Tang Z, Yu H, Lu C, Liu P, Jin X (2019b) Single-trial classification of different movements on one arm based on ERD\/ERS and Corticomuscular coherence. IEEE Access 7:128185\u2013128197. https:\/\/doi.org\/10.1109\/ACCESS.2019.2940034","journal-title":"IEEE Access"},{"key":"10703_CR42","doi-asserted-by":"publisher","unstructured":"Tuohy S, O\u2019Cualain D, Jones E, Glavin M et al (2010) Distance Determi- nation for an automobile environment using inverse perspective mapping in OpenCV. In: IET Irish signals and systems conference (ISSC 2010), pp 100\u2013105. https:\/\/doi.org\/10.1049\/cp.2010.0495","DOI":"10.1049\/cp.2010.0495"},{"issue":"1","key":"10703_CR43","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/tits.2007.908572","volume":"9","author":"CCR Wang","year":"2008","unstructured":"Wang CCR, Lien JJJ et al (2008) Automatic vehicle detection using local features\u2014a statistical approach. IEEE Trans Intell Transp Syst 9(1):83\u201396. https:\/\/doi.org\/10.1109\/tits.2007.908572","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"10703_CR44","unstructured":"WHO (2020) http:\/\/www.who.int\/mediacentre\/factsheets\/fs358\/en\/. URL http:\/\/www.who.int\/mediacentre\/factsheets\/fs358\/en\/"},{"issue":"5","key":"10703_CR45","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1109\/TSMC.2016.2616490","volume":"48","author":"W Yang","year":"2018","unstructured":"Yang W, Fang B, Yuan Y, Tang et al (2018) Fast and accurate vanishing point detection and its application in inverse perspective mapping of structured road. IEEE Trans Syst Man Cyberne Syst 48(5):755\u2013766","journal-title":"IEEE Trans Syst Man Cyberne Syst"},{"key":"10703_CR46","doi-asserted-by":"crossref","unstructured":"Yoo Y, Oh S (2016) Fast training of convolutional neural network classifiers through extreme learning machines. In: 2016 International Joint Conference on Neural Networks (IJCNN), pp 24\u201329","DOI":"10.1109\/IJCNN.2016.7727403"},{"key":"10703_CR47","doi-asserted-by":"publisher","unstructured":"Yuan Y, Chu J, Leng L, Miao J, Kim BG (2020) A scale-adaptive object-tracking algorithm with occlusion detection. J Image Video Proc 7. https:\/\/doi.org\/10.1186\/s13640-020-0496-6","DOI":"10.1186\/s13640-020-0496-6"},{"key":"10703_CR48","doi-asserted-by":"publisher","first-page":"24023","DOI":"10.1109\/ACCESS.2017.2770178","volume":"5","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Wan B, Liu W et al (2017) Vehicle motion detection using CNN. IEEE Access 5:24023\u201324031","journal-title":"IEEE Access"},{"issue":"2","key":"10703_CR49","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1109\/TPAMI.2018.2797062","volume":"41","author":"T Zhang","year":"2019","unstructured":"Zhang T, Xu C, Yang MH (2019) Learning multi-task correlation particle filters for visual tracking. IEEE Trans Pattern Anal Mach Intell 41(2):365\u2013378","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"10703_CR50","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.3390\/s20041010","volume":"20","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Chu J, Leng L, Miao J et al (2020) Mask-refined R-CNN: a network for refining object details in instance segmentation. Sensors 20(4):1010\u20131010. https:\/\/doi.org\/10.3390\/s20041010","journal-title":"Sensors"},{"key":"10703_CR51","unstructured":"Zhao Z, Yu S, Wu X, Wang C, Xu Y (2009) A multi-target tracking algorithm using texture for real-time surveillance. IEEE International Conference on Robotics and Biomimetics pp 2008:2150\u20132155"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10703-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-10703-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10703-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T05:09:42Z","timestamp":1621919382000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-10703-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,10]]},"references-count":52,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2021,6]]}},"alternative-id":["10703"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-10703-8","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2021,3,10]]},"assertion":[{"value":"9 June 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 February 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 March 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}