{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T09:15:28Z","timestamp":1762161328733},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T00:00:00Z","timestamp":1507852800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1007\/s00521-017-3235-x","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T08:25:45Z","timestamp":1507883145000},"page":"329-341","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["2D recurrent neural networks: a high-performance tool for robust visual tracking in dynamic scenes"],"prefix":"10.1007","volume":"29","author":[{"given":"Giovanni","family":"Masala","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Filippo","family":"Casu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruno","family":"Golosio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrico","family":"Grosso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,10,13]]},"reference":[{"issue":"2","key":"3235_CR1","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.cviu.2003.06.005","volume":"92","author":"H Denman","year":"2003","unstructured":"Denman H, Rea N, Kokaram A (2003) Content-based analysis for video from snooker broadcasts. Comput Vis Image Underst 92(2):176\u2013195","journal-title":"Comput Vis Image Underst"},{"key":"3235_CR2","unstructured":"Kokaram A, Pitie F, Dahyot R, Rea N, Yeterian S. Content controlled image representation for sports streaming. In: Proceedings of content-based multimedia indexing (CBMI05)"},{"issue":"4","key":"3235_CR3","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1145\/1177352.1177355","volume":"38","author":"A Yilmaz","year":"2006","unstructured":"Yilmaz A, Javed O, Shah M (2006) Object tracking: a survey. ACM Comput Surv (CSUR) 38(4):13","journal-title":"ACM Comput Surv (CSUR)"},{"key":"3235_CR4","unstructured":"Hong S, You T, Kwak S, Han B. Online tracking by learning discriminative saliency map with convolutional neural network. ArXiv preprint arXiv:1502.06796"},{"key":"3235_CR5","unstructured":"Bao C, Wu Y, Ling H, Ji H (2012) Real time robust L1 tracker using accelerated proximal gradient approach. In: 2012 IEEE conference on computer vision and pattern recognition (CVPR), IEEE, pp 1830\u20131837"},{"key":"3235_CR6","doi-asserted-by":"crossref","unstructured":"Jia X, Lu H, Yang M-H (2012) Visual tracking via adaptive structural local sparse appearance model. In: 2012 IEEE conference on computer vision and pattern recognition (CVPR), IEEE, pp 1822\u20131829","DOI":"10.1109\/CVPR.2012.6247880"},{"key":"3235_CR7","doi-asserted-by":"crossref","unstructured":"Mei X, Ling H (2009) Robust visual tracking using L1 minimization. In: 2009 IEEE 12th international conference on computer vision, IEEE, pp 1436\u20131443","DOI":"10.1109\/ICCV.2009.5459292"},{"issue":"8","key":"3235_CR8","doi-asserted-by":"crossref","first-page":"1619","DOI":"10.1109\/TPAMI.2010.226","volume":"33","author":"B Babenko","year":"2011","unstructured":"Babenko B, Yang M-H, Belongie S (2011) Robust object tracking with online multiple instance learning. IEEE Trans Pattern Anal Mach Intell 33(8):1619\u20131632","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3235_CR9","doi-asserted-by":"crossref","unstructured":"Hare S, Saffari A, Torr PH (2011) Struck: structured output tracking with kernels. In: 2011 IEEE international conference on computer vision (ICCV), IEEE, pp 263\u2013270","DOI":"10.1109\/ICCV.2011.6126251"},{"key":"3235_CR10","doi-asserted-by":"crossref","unstructured":"Grabner H, Grabner M, Bischof H (2006) Real-time tracking via on-line boosting. In: BMVC, vol 1, p 6","DOI":"10.5244\/C.20.6"},{"issue":"11","key":"3235_CR11","doi-asserted-by":"crossref","first-page":"2188","DOI":"10.1109\/TPAMI.2011.70","volume":"33","author":"J Gall","year":"2011","unstructured":"Gall J, Yao A, Razavi N, Van Gool L, Lempitsky V (2011) Hough forests for object detection, tracking, and action recognition. IEEE Trans Pattern Anal Mach Intell 33(11):2188\u20132202","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3235_CR12","doi-asserted-by":"crossref","unstructured":"Schulter S, Leistner C, Roth PM, Bischof H, Van Gool LJ (2011) On-line hough forests. In: BMVC, pp 1\u201311","DOI":"10.5244\/C.25.128"},{"key":"3235_CR13","doi-asserted-by":"crossref","unstructured":"Henriques JF, Caseiro R, Martins P, Batista J (2012) Exploiting the circulant structure of tracking-by-detection with kernels. In: Proceedings of the European conference on computer vision","DOI":"10.1007\/978-3-642-33765-9_50"},{"key":"3235_CR14","doi-asserted-by":"crossref","unstructured":"Danelljan M, Khan FS, Felsberg M, van de Weijer J (2014) Adaptive color attributes for real-time visual tracking. In: 2014 IEEE conference on computer vision and pattern recognition (CVPR), June 2014, pp 1090\u20131097","DOI":"10.1109\/CVPR.2014.143"},{"key":"3235_CR15","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.neucom.2013.04.016","volume":"120","author":"X Wang","year":"2013","unstructured":"Wang X, Ma L, Wang B, Wang T (2013) A hybrid optimization-based recurrent neural network for real-time data prediction. Neurocomputing 120:547\u2013559","journal-title":"Neurocomputing"},{"issue":"2","key":"3235_CR16","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1207\/s15516709cog1402_1","volume":"14","author":"JL Elman","year":"1990","unstructured":"Elman JL (1990) Finding structure in time. Cogn Sci 14(2):179\u2013211","journal-title":"Cogn Sci"},{"key":"3235_CR17","doi-asserted-by":"crossref","unstructured":"Ondruska P, Posner I (2016) Deep tracking: seeing beyond seeing using recurrent neural networks. In: AAAI-16 conference, 12\u201317 Feb, Phoenix, Arizona USA","DOI":"10.1609\/aaai.v30i1.10413"},{"key":"3235_CR18","doi-asserted-by":"crossref","unstructured":"Korekado K, Morie T, Nomura O, Ando H, Nakano T, Matsugu M, Iwata A (2003) A convolutional neural network vlsi for image recognition using merged\/mixed analog-digital architecture. In: Knowledge-based intelligent information and engineering systems, pp 169\u2013176. Springer","DOI":"10.1007\/978-3-540-45226-3_24"},{"key":"3235_CR19","unstructured":"Sermanet P et al (2013) OverFeat: integrated recognition, localization and detection using convolutional networks. In: International conference on learning representations (ICLR 2014), 16, CBLS"},{"key":"3235_CR20","doi-asserted-by":"crossref","unstructured":"Girshick R, Donahue J, Darrell T, Malik J (2014) Rich feature hierarchies for accurate object detection and semantic segmentation, CVPR","DOI":"10.1109\/CVPR.2014.81"},{"key":"3235_CR21","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2014) Spatial pyramid pooling in deep convolutional networks for visual recognition, ECCV","DOI":"10.1007\/978-3-319-10578-9_23"},{"key":"3235_CR22","unstructured":"Shaoqing R et al (2015) Faster R-CNN: towards real-time object detection with region proposal networks. In: Advances in neural information processing systems (NIPS)"},{"key":"3235_CR23","unstructured":"Redmon J et al (2015) You only look once: unified, real-time object detection. arXiv:1506.02640"},{"key":"3235_CR24","doi-asserted-by":"crossref","unstructured":"Bertinetto L, Valmadre J, Henriques JF, Vedaldi A, Torr PH (2016). Fully-convolutional siamese networks for object tracking. In: European conference on computer vision, pp 850\u2013865. Springer","DOI":"10.1007\/978-3-319-48881-3_56"},{"key":"3235_CR25","doi-asserted-by":"crossref","unstructured":"Masala GL, Golosio B, Tistarelli M, Grosso E (2016) 2D recurrent neural networks for robust visual tracking of non-rigid bodies. In: International conference on engineering applications of neural networks, pp 18\u201334. Springer","DOI":"10.1007\/978-3-319-44188-7_2"},{"key":"3235_CR26","unstructured":"Briechle K, Hanebeck UD (2001) Template matching using fast normalized cross correlation. In: Aerospace\/defense sensing, simulation, and controls. International Society for Optics and Photonics, pp 95\u2013102"},{"key":"3235_CR27","doi-asserted-by":"crossref","unstructured":"Bradski GR (1998) Real time face and object tracking as a component of a perceptual user interface. In: Proceedings of the fourth IEEE workshop on applications of computer vision (WACV \u201898), pp 214, 219, 19\u201321 Oct 1998","DOI":"10.1109\/ACV.1998.732882"},{"issue":"7","key":"3235_CR28","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1016\/j.engappai.2003.10.004","volume":"16","author":"S \u015eeker","year":"2003","unstructured":"\u015eeker S, Ayaz E, T\u00fcrkcan E (2003) Elman\u2019s recurrent neural network applications to condition monitoring in nuclear power plant and rotating machinery. Eng Appl Artif Intell 16(7):647\u2013656","journal-title":"Eng Appl Artif Intell"},{"key":"3235_CR29","volume-title":"Neural networks: a comprehensive foundation","author":"S Haykin","year":"1998","unstructured":"Haykin S (1998) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall PTR, Upper Saddle River","edition":"2"},{"key":"3235_CR30","unstructured":"Dataset: final of triple jump at the London 2012 Summer Olympics available on the YouTube platform. https:\/\/www.youtube.com\/watch?v=GeYfshPYyZ8"},{"key":"3235_CR31","doi-asserted-by":"publisher","unstructured":"Liu R, Wang D, Han Y, Fan X, Luo Z (2017) Adaptive low-rank subspace learning with online optimization for robust visual tracking. Neural networks, vol 88, April 2017, pp 90\u2013104, ISSN 0893-6080. doi: 10.1016\/j.neunet.2017.02.002","DOI":"10.1016\/j.neunet.2017.02.002"},{"issue":"7","key":"3235_CR32","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1109\/TPAMI.2013.230","volume":"36","author":"AW Smeulders","year":"2014","unstructured":"Smeulders AW, Chu DM, Cucchiara R, Calderara S, Dehghan A, Shah M (2014) Visual tracking: an experimental survey. IEEE Trans Pattern Anal Mach Intell 36(7):1442\u20131468","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3235_CR33","doi-asserted-by":"crossref","unstructured":"Stewart R, Andriluka M (2016) End-to-end people detection in crowded scenes. In: 29th IEEE conference on computer vision and pattern recognition. IEEE Computer Society, Los Alamitos, CA","DOI":"10.1109\/CVPR.2016.255"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-017-3235-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3235-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3235-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T15:09:36Z","timestamp":1659625776000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-017-3235-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,13]]},"references-count":33,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["3235"],"URL":"https:\/\/doi.org\/10.1007\/s00521-017-3235-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,10,13]]}}}