{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T14:27:55Z","timestamp":1781879275787,"version":"3.54.5"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T00:00:00Z","timestamp":1567123200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,30]],"date-time":"2019-08-30T00:00:00Z","timestamp":1567123200000},"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":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s12652-019-01429-5","type":"journal-article","created":{"date-parts":[[2019,8,31]],"date-time":"2019-08-31T06:20:02Z","timestamp":1567232402000},"page":"1603-1614","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Multiple vehicle tracking and classification system with a convolutional neural network"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4116-3941","authenticated-orcid":false,"given":"HyungJun","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,8,30]]},"reference":[{"key":"1429_CR1","doi-asserted-by":"publisher","first-page":"113","DOI":"10.3141\/2645-13","volume":"2645","author":"Y Adu-Gyamfi","year":"2017","unstructured":"Adu-Gyamfi Y, Asare S, Sharma A, Titus T (2017) Automated vehicle recognition with deep convolutional neural networks. Transport Res Record J Transport Res Board 2645:113\u2013122","journal-title":"Transport Res Record J Transport Res Board"},{"issue":"3","key":"1429_CR2","doi-asserted-by":"publisher","first-page":"219","DOI":"10.2174\/2213275910801030219","volume":"1","author":"T Bouwmans","year":"2008","unstructured":"Bouwmans T, Baf FEl, Vachon B (2008) Background modeling using mixture of Gaussians for foreground detection\u2014a survey. Recent Patents Comput Sci 1(3):219\u2013237","journal-title":"Recent Patents Comput Sci"},{"issue":"3","key":"1429_CR3","doi-asserted-by":"publisher","first-page":"920","DOI":"10.1109\/TITS.2011.2119372","volume":"12","author":"N Buch","year":"2011","unstructured":"Buch N, Velastin SA, Orwell J (2011) A review of computer vision techniques for the analysis of urban traffic. IEEE Trans Intell Transport Syst 12(3):920\u2013939","journal-title":"IEEE Trans Intell Transport Syst"},{"issue":"6","key":"1429_CR4","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","volume":"8","author":"JF Canny","year":"1986","unstructured":"Canny JF (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 8(6):679\u2013698","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1429_CR5","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/978-3-319-75608-0_9","volume":"728","author":"S Capobianco","year":"2018","unstructured":"Capobianco S, Facheris L, Cuccoli F, Marinai S (2018) Vehicle classification based on convolutional networks applied to FM-CW radar signals. Adv Intell Syst Comput 728:115\u2013128","journal-title":"Adv Intell Syst Comput"},{"key":"1429_CR6","unstructured":"Cathey FW, Dailey DJ (2004) One-parameter camera calibration for traffic management cameras. In: IEEE intelligent transportation systems conference, Washington, D.C., pp.865-869"},{"key":"1429_CR7","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1109\/TPAMI.2003.1233909","volume":"25","author":"R Cucchiara","year":"2003","unstructured":"Cucchiara R, Piccardi M, Prati A (2003) Detecting moving objects, ghosts, and shadows in video streams. IEEE Trans Pattern Anal Mach Intell 25:1337\u20131342","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1429_CR8","doi-asserted-by":"publisher","DOI":"10.1561\/9781601988157","volume-title":"Deep learning: methods and applications","author":"L Deng","year":"2014","unstructured":"Deng L, Yu D (2014) Deep learning: methods and applications. Now Publishers Inc., Boston"},{"issue":"4","key":"1429_CR9","doi-asserted-by":"publisher","first-page":"2247","DOI":"10.1109\/TITS.2015.2402438","volume":"16","author":"Z Dong","year":"2015","unstructured":"Dong Z, Wu Y, Pei M, Jia Y (2015) Vehicle type classification using a semisupervised convolutional neural network. IEEE Trans Intell Transport Syst 16(4):2247\u20132256","journal-title":"IEEE Trans Intell Transport Syst"},{"key":"1429_CR10","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/361237.361242","volume":"15","author":"RO Duda","year":"1972","unstructured":"Duda RO, Hart PE (1972) Use of the Hough transform to detect lines and curves in pictures. Commun ACM 15:11\u201315","journal-title":"Commun ACM"},{"key":"1429_CR11","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.patcog.2007.04.003","volume":"41","author":"AF Fernandes","year":"2008","unstructured":"Fernandes AF, Oliveria MM (2008) Real-time line detection through an improved Hough transform voting scheme. Pattern Recogn 41:299\u2013314","journal-title":"Pattern Recogn"},{"issue":"9","key":"1429_CR12","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"K He","year":"2015","unstructured":"He K, Zhang X, Ren S, Sun J (2015) Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans Pattern Anal Mach Intell 37(9):1904\u20131916","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2B","key":"1429_CR13","first-page":"1491","volume":"16","author":"H Kim","year":"2013","unstructured":"Kim H (2013a) Image processing based multiple vehicle monitoring system. Inf Int Interdiscip J 16(2B):1491\u20131496","journal-title":"Inf Int Interdiscip J"},{"issue":"3B","key":"1429_CR14","first-page":"2305","volume":"16","author":"H Kim","year":"2013","unstructured":"Kim H (2013b) Detecting moving objects using background modeling and local binary patterns. Inf Int Interdiscip J 16(3B):2305\u20132310","journal-title":"Inf Int Interdiscip J"},{"key":"1429_CR15","doi-asserted-by":"crossref","unstructured":"Kim P, Lim K (2017) Vehicle type classification using bagging and convolutional neural network on multi view surveillance image. In: 2017 IEEE conference on computer vision and pattern recognition workshops, Honolulu, pp 41\u201346","DOI":"10.1109\/CVPRW.2017.126"},{"key":"1429_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/rs10010124","volume":"10","author":"Y Koga","year":"2018","unstructured":"Koga Y, Miyazaki H, Shibasaki R (2018) A CNN-based method of vehicle detection from aerial images using hard example mining. Remote Sens 10:1\u201321","journal-title":"Remote Sens"},{"issue":"2","key":"1429_CR17","first-page":"1106","volume":"25","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) ImageNet classification with deep convolutional neural networks. Adv Neural Inf Process Syst 25(2):1106\u20131114","journal-title":"Adv Neural Inf Process Syst"},{"key":"1429_CR18","doi-asserted-by":"crossref","unstructured":"Manana M, Tu C, Owolawi PA (2017) A survey on vehicle detection based on convolution neural networks. In: 3rd IEEE international conference on computer and communications, Chengdu, pp\u00a01751\u20131755","DOI":"10.1109\/CompComm.2017.8322840"},{"key":"1429_CR19","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/BF01215814","volume":"8","author":"NBJ McFarlane","year":"1995","unstructured":"McFarlane NBJ, Schofield CP (1995) Segmentation and tracking of piglets in images. Mach Vis Appl 8:187\u2013193","journal-title":"Mach Vis Appl"},{"issue":"2","key":"1429_CR20","first-page":"183","volume":"12","author":"K Mu","year":"2016","unstructured":"Mu K, Hui F, Zhao X (2016) Multiple vehicle detection and tracking in highway traffic surveillance video based on SIFT feature matching. J Inf Process Syst 12(2):183\u2013195","journal-title":"J Inf Process Syst"},{"key":"1429_CR21","unstructured":"Nair V, Hinton GE (2010) Rectified linear units improve restricted Boltzmann machines. In: Proceedings of the 27th international conference on machine learning, pp\u00a0807\u2013814"},{"key":"1429_CR22","unstructured":"Piccardi M (2014) Background subtraction techniques: a review. In: IEEE international conference on systems, man and cybernetics, pp\u00a03099\u20133104"},{"issue":"9\u201310","key":"1429_CR23","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1016\/S0262-8856(02)00054-9","volume":"20","author":"R Rother","year":"2002","unstructured":"Rother R (2002) A new approach to vanishing point detection in architectural environments. Image Vis Comput 20(9\u201310):647\u2013655","journal-title":"Image Vis Comput"},{"issue":"2","key":"1429_CR24","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/TITS.2003.821213","volume":"4","author":"TN Schoepflin","year":"2003","unstructured":"Schoepflin TN, Dailey DJ (2003) Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation. IEEE Trans Intell Transport Syst 4(2):90\u201398","journal-title":"IEEE Trans Intell Transport Syst"},{"key":"1429_CR25","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.cviu.2013.12.005","volume":"122","author":"A Sobral","year":"2014","unstructured":"Sobral A, Vacavant A (2014) A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos. Comput Vis Image Underst 122:4\u201321","journal-title":"Comput Vis Image Underst"},{"issue":"8","key":"1429_CR26","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1109\/34.868677","volume":"22","author":"C Stauffer","year":"2000","unstructured":"Stauffer C, Grimson WEL (2000) Learning patterns of activity using real-time tracking. IEEE Trans Pattern Anal Mach Intell 22(8):747\u2013757","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-019-01429-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-019-01429-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-019-01429-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T18:16:25Z","timestamp":1695147385000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-019-01429-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,30]]},"references-count":26,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["1429"],"URL":"https:\/\/doi.org\/10.1007\/s12652-019-01429-5","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,30]]},"assertion":[{"value":"16 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 August 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}