{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T16:04:06Z","timestamp":1769270646105,"version":"3.49.0"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T00:00:00Z","timestamp":1564099200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T00:00:00Z","timestamp":1564099200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1007\/s00521-019-04365-9","type":"journal-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T19:02:23Z","timestamp":1564167743000},"page":"8585-8597","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Human action recognition with bag of visual words using different machine learning methods and hyperparameter optimization"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7549-0137","authenticated-orcid":false,"given":"Muhammet Fatih","family":"Aslan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akif","family":"Durdu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kadir","family":"Sabanci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,26]]},"reference":[{"key":"4365_CR1","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.procs.2015.08.050","volume":"58","author":"T Dobhal","year":"2015","unstructured":"Dobhal T, Shitole V, Thomas G, Navada G (2015) Human activity recognition using binary motion image and deep learning. Procedia Comput Sci 58:178\u2013185","journal-title":"Procedia Comput Sci"},{"issue":"1","key":"4365_CR2","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/MPRV.2010.7","volume":"9","author":"E Kim","year":"2010","unstructured":"Kim E, Helal S, Cook D (2010) Human activity recognition and pattern discovery. IEEE Pervasive Comput\/IEEE Comput Soc IEEE Commun Soc 9(1):48","journal-title":"IEEE Pervasive Comput\/IEEE Comput Soc IEEE Commun Soc"},{"key":"4365_CR3","doi-asserted-by":"publisher","first-page":"13","DOI":"10.3389\/fnbot.2014.00013","volume":"8","author":"R De Kleijn","year":"2014","unstructured":"De Kleijn R, Kachergis G, Hommel B (2014) Everyday robotic action: lessons from human action control. Front Neurorobot 8:13","journal-title":"Front Neurorobot"},{"key":"4365_CR4","unstructured":"Dhamsania CJ, Ratanpara TV (2016) A survey on human action recognition from videos. In: 2016 Online international conference on green engineering and technologies (IC-GET). IEEE, pp 1\u20135"},{"issue":"8","key":"4365_CR5","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1049\/iet-cvi.2016.0355","volume":"11","author":"M Koohzadi","year":"2017","unstructured":"Koohzadi M, Charkari NM (2017) Survey on deep learning methods in human action recognition. IET Comput Vis 11(8):623\u2013632","journal-title":"IET Comput Vis"},{"issue":"5","key":"4365_CR6","first-page":"166","volume":"7","author":"LQ Ngoc","year":"2016","unstructured":"Ngoc LQ, Viet VH, Son TT, Hoang PM (2016) A robust approach for action recognition based on spatio-temporal features in RGB-D sequences. Int J Adv Comput Sci Appl 7(5):166\u2013177","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"2","key":"4365_CR7","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91\u2013110","journal-title":"Int J Comput Vis"},{"key":"4365_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3444-y","author":"R Mandal","year":"2018","unstructured":"Mandal R, Roy PP, Pal U, Blumenstein M (2018) Bag-of-visual-words for signature-based multi-script document retrieval. Neural Comput Appl. \n                  https:\/\/doi.org\/10.1007\/s00521-018-3444-y","journal-title":"Neural Comput Appl"},{"key":"4365_CR9","doi-asserted-by":"crossref","unstructured":"Tang F, Lim SH, Chang NL, Tao H (2009) A novel feature descriptor invariant to complex brightness changes. In: 2009 IEEE conference on computer vision and pattern recognition. IEEE, pp 2631\u20132638","DOI":"10.1109\/CVPR.2009.5206550"},{"key":"4365_CR10","doi-asserted-by":"crossref","unstructured":"Bay H, Tuytelaars T, Van Gool L (2006) Surf: speeded up robust features. In: European conference on computer vision. Springer, pp 404\u2013417","DOI":"10.1007\/11744023_32"},{"issue":"2","key":"4365_CR11","first-page":"323","volume":"1","author":"P Panchal","year":"2013","unstructured":"Panchal P, Panchal S, Shah S (2013) A comparison of SIFT and SURF. Int J Innov Res Comput and Commun Eng 1(2):323\u2013327","journal-title":"Int J Innov Res Comput and Commun Eng"},{"key":"4365_CR12","unstructured":"Karami E, Prasad S, Shehata M (2017) Image matching using SIFT, SURF, BRIEF and ORB: performance comparison for distorted images. arXiv preprint \n                  arXiv:1710.02726"},{"key":"4365_CR13","doi-asserted-by":"crossref","unstructured":"Yang J, Jiang Y-G, Hauptmann AG, Ngo C-W (2007) Evaluating bag-of-visual-words representations in scene classification. In: Proceedings of the international workshop on multimedia information retrieval. ACM, pp 197\u2013206","DOI":"10.1145\/1290082.1290111"},{"issue":"3","key":"4365_CR14","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1049\/iet-cvi.2014.0018","volume":"9","author":"M Faraki","year":"2014","unstructured":"Faraki M, Palhang M, Sanderson C (2014) Log-Euclidean bag of words for human action recognition. IET Comput Vis 9(3):331\u2013339","journal-title":"IET Comput Vis"},{"issue":"3","key":"4365_CR15","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s00371-015-1066-2","volume":"32","author":"DD Dawn","year":"2016","unstructured":"Dawn DD, Shaikh SH (2016) A comprehensive survey of human action recognition with spatio-temporal interest point (STIP) detector. Vis Comput 32(3):289\u2013306","journal-title":"Vis Comput"},{"issue":"2","key":"4365_CR16","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1109\/LGRS.2009.2035644","volume":"7","author":"S Xu","year":"2010","unstructured":"Xu S, Fang T, Li D, Wang S (2010) Object classification of aerial images with bag-of-visual words. IEEE Geosci Remote Sens Lett 7(2):366\u2013370","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"4365_CR17","first-page":"48109","volume":"1001","author":"J Kim","year":"2012","unstructured":"Kim J, Kim B-S, Savarese S (2012) Comparing image classification methods: k-nearest-neighbor and support-vector-machines. Ann Arbor 1001:48109\u201348122","journal-title":"Ann Arbor"},{"issue":"4","key":"4365_CR18","doi-asserted-by":"publisher","first-page":"1937","DOI":"10.1016\/j.eswa.2013.08.089","volume":"41","author":"DM Farid","year":"2014","unstructured":"Farid DM, Zhang L, Rahman CM, Hossain MA, Strachan R (2014) Hybrid decision tree and na\u00efve Bayes classifiers for multi-class classification tasks. Expert Syst Appl 41(4):1937\u20131946","journal-title":"Expert Syst Appl"},{"key":"4365_CR19","doi-asserted-by":"crossref","unstructured":"Ben-Hur A, Weston J (2010) A user\u2019s guide to support vector machines. In: Data mining techniques for the life sciences. Springer, pp 223\u2013239","DOI":"10.1007\/978-1-60327-241-4_13"},{"issue":"6","key":"4365_CR20","doi-asserted-by":"publisher","first-page":"247","DOI":"10.3390\/e19060247","volume":"19","author":"J Abell\u00e1n","year":"2017","unstructured":"Abell\u00e1n J, Castellano JG (2017) Improving the Naive Bayes classifier via a quick variable selection method using maximum of entropy. Entropy 19(6):247","journal-title":"Entropy"},{"issue":"Feb","key":"4365_CR21","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra J, Bengio Y (2012) Random search for hyper-parameter optimization. J Mach Learn Res 13(Feb):281\u2013305","journal-title":"J Mach Learn Res"},{"key":"4365_CR22","doi-asserted-by":"crossref","unstructured":"Yao Y, Cao J, Ma Z (2018) A cost-effective deadline-constrained scheduling strategy for a hyperparameter optimization workflow for machine learning algorithms. In: International conference on service-oriented computing. Springer, pp 870\u2013878","DOI":"10.1007\/978-3-030-03596-9_62"},{"key":"4365_CR23","doi-asserted-by":"crossref","unstructured":"Schuldt C, Laptev I, Caputo B (2004) Recognizing human actions: a local SVM approach. In: Proceedings of the 17th international conference on pattern recognition, 2004 ICPR 2004, vol. 3. IEEE, pp 32\u201336","DOI":"10.1109\/ICPR.2004.1334462"},{"key":"4365_CR24","doi-asserted-by":"crossref","unstructured":"Blank M, Gorelick L, Shechtman E, Irani M, Basri R (2005) Actions as space\u2013time shapes. In: Proceedings of international conference computer Vision. IEEE, pp 1395\u20131402","DOI":"10.1109\/ICCV.2005.28"},{"issue":"8","key":"4365_CR25","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","volume":"31","author":"AK Jain","year":"2010","unstructured":"Jain AK (2010) Data clustering: 50\u00a0years beyond K-means. Pattern Recognit Lett 31(8):651\u2013666","journal-title":"Pattern Recognit Lett"},{"issue":"5","key":"4365_CR26","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/MC.2018.2381112","volume":"51","author":"T Pl\u00f6tz","year":"2018","unstructured":"Pl\u00f6tz T, Guan Y (2018) Deep learning for human activity recognition in mobile computing. Computer 51(5):50\u201359","journal-title":"Computer"},{"key":"4365_CR27","doi-asserted-by":"crossref","unstructured":"Baccouche M, Mamalet F, Wolf C, Garcia C, Baskurt A (2011) Sequential deep learning for human action recognition. In: International workshop on human behavior understanding. Springer, pp 29\u201339","DOI":"10.1007\/978-3-642-25446-8_4"},{"issue":"3","key":"4365_CR28","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1049\/iet-cvi.2011.0185","volume":"6","author":"S Rahman","year":"2012","unstructured":"Rahman S, Cho S-Y, Leung M (2012) Recognising human actions by analysing negative spaces. IET Comput Vis 6(3):197\u2013213","journal-title":"IET Comput Vis"},{"key":"4365_CR29","doi-asserted-by":"crossref","unstructured":"Zhang Z, Hu Y, Chan S, Chia L-T (2008) Motion context: a new representation for human action recognition. In: European conference on computer vision. Springer, pp 817\u2013829","DOI":"10.1007\/978-3-540-88693-8_60"},{"issue":"9","key":"4365_CR30","doi-asserted-by":"publisher","first-page":"1280","DOI":"10.1109\/TCSVT.2008.928888","volume":"18","author":"M Singh","year":"2008","unstructured":"Singh M, Basu A, Mandal MK (2008) Human activity recognition based on silhouette directionality. IEEE Trans Circuits Syst Video Technol 18(9):1280\u20131292","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"2","key":"4365_CR31","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1109\/TSMCB.2011.2166761","volume":"42","author":"W Bian","year":"2012","unstructured":"Bian W, Tao D, Rui Y (2012) Cross-domain human action recognition. IEEE Trans Syst Man Cybern Part B (Cybern) 42(2):298\u2013307","journal-title":"IEEE Trans Syst Man Cybern Part B (Cybern)"},{"issue":"5","key":"4365_CR32","doi-asserted-by":"publisher","first-page":"1581","DOI":"10.1109\/TFUZZ.2014.2370678","volume":"23","author":"X-Q Cao","year":"2015","unstructured":"Cao X-Q, Liu Z-Q (2015) Type-2 fuzzy topic models for human action recognition. IEEE Trans Fuzzy Syst 23(5):1581\u20131593","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"11","key":"4365_CR33","doi-asserted-by":"publisher","first-page":"391","DOI":"10.5772\/57054","volume":"10","author":"MZ Uddin","year":"2013","unstructured":"Uddin MZ, Kim T-S, Kim J-T (2013) A spatiotemporal robust approach for human activity recognition. Int J Adv Robot Syst 10(11):391","journal-title":"Int J Adv Robot Syst"},{"key":"4365_CR34","doi-asserted-by":"crossref","unstructured":"Ding W, Liu K, Cheng F, Shi H, Zhang B (2015) Skeleton-based human action recognition with profile hidden Markov models. In: CCF Chinese conference on computer vision. Springer, pp 12\u201321","DOI":"10.1007\/978-3-662-48558-3_2"},{"key":"4365_CR35","unstructured":"Gao H, Chen W, Dou L (2015) Image classification based on support vector machine and the fusion of complementary features. arXiv preprint \n                  arXiv:1511.01706"},{"issue":"4","key":"4365_CR36","first-page":"331","volume":"10","author":"NB Halima","year":"2016","unstructured":"Halima NB, Hosam O (2016) Bag of words based surveillance system using support vector machines. Int J Secur Appl 10(4):331\u2013346","journal-title":"Int J Secur Appl"},{"issue":"13","key":"4365_CR37","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1049\/el.2013.1481","volume":"49","author":"A-A Liu","year":"2013","unstructured":"Liu A-A, Su Y, Gao Z, Hao T, Yang Z-X, Zhang Z (2013) Partwise bag-of-words-based multi-task learning for human action recognition. Electron Lett 49(13):803\u2013805","journal-title":"Electron Lett"},{"key":"4365_CR38","doi-asserted-by":"publisher","first-page":"544","DOI":"10.1016\/j.neucom.2014.04.090","volume":"151","author":"A-A Liu","year":"2015","unstructured":"Liu A-A, Xu N, Su Y-T, Lin H, Hao T, Yang Z-X (2015) Single\/multi-view human action recognition via regularized multi-task learning. Neurocomputing 151:544\u2013553","journal-title":"Neurocomputing"},{"issue":"3","key":"4365_CR39","first-page":"35","volume":"11","author":"Y Liu","year":"2018","unstructured":"Liu Y, Fung K-C, Ding W, Guo H, Qu T, Xiao C (2018) Novel smart waste sorting system based on image processing algorithms: SURF-BoW and multi-class SVM. Comput Inf Sci 11(3):35","journal-title":"Comput Inf Sci"},{"issue":"1","key":"4365_CR40","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1109\/JSTSP.2012.2234722","volume":"7","author":"Y Zhu","year":"2013","unstructured":"Zhu Y, Nayak NM, Roy-Chowdhury AK (2013) Context-aware activity recognition and anomaly detection in video. J Sel Top Signal Process 7(1):91\u2013101","journal-title":"J Sel Top Signal Process"},{"key":"4365_CR41","unstructured":"Vo V, Ly N (2012) Robust human action recognition using improved BOW and hybrid features. In: 2012 IEEE International symposium on signal processing and information technology (ISSPIT). IEEE, pp 000224\u2013000229"},{"key":"4365_CR42","doi-asserted-by":"crossref","unstructured":"Gilbert A, Illingworth J, Bowden R (2009) Fast realistic multi-action recognition using mined dense spatio-temporal features. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 925\u2013931","DOI":"10.1109\/ICCV.2009.5459335"},{"key":"4365_CR43","doi-asserted-by":"crossref","unstructured":"Grushin A, Monner DD, Reggia JA, Mishra A (2013) Robust human action recognition via long short-term memory. In: The 2013 international joint conference on, neural networks (IJCNN). IEEE, pp 1\u20138","DOI":"10.1109\/IJCNN.2013.6706797"},{"key":"4365_CR44","doi-asserted-by":"crossref","unstructured":"Jhuang H, Serre T, Wolf L, Poggio T (2007) A biologically inspired system for action recognition. In: IEEE 11th international conference on computer vision, 2007 ICCV 2007. IEEE, pp 1\u20138","DOI":"10.1109\/ICCV.2007.4408988"},{"key":"4365_CR45","unstructured":"Kl\u00e4ser A (2010) Learning human actions in video. Ph.D. Thesis, Universit\u00e9 de Grenoble"},{"key":"4365_CR46","doi-asserted-by":"crossref","unstructured":"Lin Z, Jiang Z, Davis LS (2009) Recognizing actions by shape-motion prototype trees. In: 2009 IEEE 12th international conference on computer vision. IEEE, pp 444\u2013451","DOI":"10.1109\/ICCV.2009.5459184"},{"key":"4365_CR47","doi-asserted-by":"crossref","unstructured":"Liu J, Luo J, Shah M (2009) Recognizing realistic actions from videos \u201cin the wild\u201d. In: IEEE conference on computer vision and pattern recognition, 2009. CVPR 2009. IEEE, pp 1996\u20132003","DOI":"10.1109\/CVPR.2009.5206744"},{"key":"4365_CR48","unstructured":"Liu J, Shah M (2008) Learning human actions via information maximization. In: IEEE conference on computer vision and pattern recognition, 2008. CVPR 2008. IEEE, pp 1\u20138"},{"key":"4365_CR49","unstructured":"Rodriguez M (2010) Spatio-temporal maximum average correlation height templates in action recognition and video summarization. Electronic Theses and Dissertations, 4323"},{"key":"4365_CR50","unstructured":"Schindler K, Van Gool L (2008) Action snippets: How many frames does human action recognition require? In: IEEE conference on computer vision and pattern recognition CVPR 2008. IEEE, pp 1\u20138"},{"key":"4365_CR51","unstructured":"Sun X, Chen M, Hauptmann A (2009) Action recognition via local descriptors and holistic features. In: IEEE computer society conference on computer vision and pattern recognition workshops, 2009 CVPR workshops 2009. IEEE, pp 58\u201365"},{"key":"4365_CR52","doi-asserted-by":"crossref","unstructured":"Veeriah V, Zhuang N, Qi G-J (2015) Differential recurrent neural networks for action recognition. In: Proceedings of the IEEE international conference on computer vision, pp 4041\u20134049","DOI":"10.1109\/ICCV.2015.460"},{"key":"4365_CR53","unstructured":"Wu X, Liang W, Jia Y (2009) Incremental discriminative-analysis of canonical correlations for action recognition. In: 2009 IEEE 12th international conference on computer vision, 2009. IEEE, pp 2035\u20132041"},{"key":"4365_CR54","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3437-x","author":"J Suto","year":"2018","unstructured":"Suto J, Oniga S, Lung C, Orha I (2018) Comparison of offline and real-time human activity recognition results using machine learning techniques. Neural Comput Appl. \n                  https:\/\/doi.org\/10.1007\/s00521-018-3437-x","journal-title":"Neural Comput Appl"},{"issue":"3","key":"4365_CR55","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/s11263-007-0122-4","volume":"79","author":"JC Niebles","year":"2008","unstructured":"Niebles JC, Wang H, Fei-Fei L (2008) Unsupervised learning of human action categories using spatial-temporal words. Int J Comput Vis 79(3):299\u2013318","journal-title":"Int J Comput Vis"},{"key":"4365_CR56","doi-asserted-by":"crossref","unstructured":"Ramage D, Hall D, Nallapati R, Manning CD (2009) Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora. In: Proceedings of the 2009 conference on empirical methods in natural language processing: volume 1. Association for Computational Linguistics, pp 248\u2013256","DOI":"10.3115\/1699510.1699543"},{"key":"4365_CR57","doi-asserted-by":"crossref","unstructured":"Blank M, Gorelick L, Shechtman E, Irani M, Basri R (2005) Actions as space\u2013time shapes. In: Tenth IEEE international conference on computer vision (ICCV\u201905). IEEE, pp 1395\u20131402","DOI":"10.1109\/ICCV.2005.28"},{"key":"4365_CR58","doi-asserted-by":"crossref","unstructured":"Scovanner P, Ali S, Shah M (2007) A 3-dimensional sift descriptor and its application to action recognition. In: Proceedings of the 15th ACM international conference on multimedia. ACM, pp 357\u2013360","DOI":"10.1145\/1291233.1291311"},{"issue":"3","key":"4365_CR59","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.1016\/j.patcog.2011.08.014","volume":"45","author":"M Bregonzio","year":"2012","unstructured":"Bregonzio M, Xiang T, Gong S (2012) Fusing appearance and distribution information of interest points for action recognition. Pattern Recognit 45(3):1220\u20131234","journal-title":"Pattern Recognit"},{"key":"4365_CR60","doi-asserted-by":"crossref","unstructured":"Doll\u00e1r P, Rabaud V, Cottrell G, Belongie S (2005) Behavior recognition via sparse spatio-temporal features. In: 2nd Joint IEEE international workshop on visual surveillance and performance evaluation of tracking and surveillance. IEEE, pp 65\u201372","DOI":"10.1109\/VSPETS.2005.1570899"},{"key":"4365_CR61","unstructured":"Klaser A, Marsza\u0142ek M, Schmid C (2008) A spatio-temporal descriptor based on 3D-gradients. In: BMVC 2008 19th British machine vision conference. British Machine Vision Association, pp 275: 1\u201310"},{"key":"4365_CR62","doi-asserted-by":"crossref","unstructured":"Liu H, Ju Z, Ji X, Chan CS, Khoury M (2017) Study of human action recognition based on improved spatio-temporal features. In: Human Motion sensing and recognition: a fuzzy qualitative approach. Springer, Berlin, pp 233\u2013250","DOI":"10.1007\/978-3-662-53692-6_11"},{"issue":"2","key":"4365_CR63","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.jare.2013.11.007","volume":"6","author":"MM Moussa","year":"2015","unstructured":"Moussa MM, Hamayed E, Fayek MB, El Nemr HA (2015) An enhanced method for human action recognition. J Adv Res 6(2):163\u2013169","journal-title":"J Adv Res"},{"key":"4365_CR64","unstructured":"Singh YK, Singh ND (2017) Binary face image recognition using logistic regression and neural network. In: 2017 International conference on energy, communication, data analytics and soft computing (ICECDS). IEEE, pp 3883\u20133888"},{"key":"4365_CR65","unstructured":"Pandey RK, Vignesh K, Ramakrishnan A (2018) Binary Document image super resolution for improved readability and OCR performance. arXiv preprint \n                  arXiv:1812.02475"},{"issue":"1\u20132","key":"4365_CR66","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/S0933-3657(02)00057-X","volume":"26","author":"P Perner","year":"2002","unstructured":"Perner P, Perner H, M\u00fcller B (2002) Mining knowledge for HEp-2 cell image classification. Artif Intel Med 26(1\u20132):161\u2013173","journal-title":"Artif Intel Med"},{"key":"4365_CR67","doi-asserted-by":"publisher","first-page":"270171","DOI":"10.1155\/2014\/270171","volume":"2014","author":"MJ Santofimia","year":"2014","unstructured":"Santofimia MJ, Martinez-del-Rincon J, Nebel J-C (2014) Episodic reasoning for vision-based human action recognition. Sci World J 2014:270171","journal-title":"Sci World J"},{"key":"4365_CR68","doi-asserted-by":"crossref","unstructured":"Laptev I, Lindeberg T (2006) Local descriptors for spatio-temporal recognition. In: Spatial coherence for visual motion analysis. Springer, pp 91\u2013103","DOI":"10.1007\/11676959_8"},{"issue":"8","key":"4365_CR69","doi-asserted-by":"publisher","first-page":"1761","DOI":"10.1016\/j.patcog.2011.01.017","volume":"44","author":"M Galar","year":"2011","unstructured":"Galar M, Fern\u00e1ndez A, Barrenechea E, Bustince H, Herrera F (2011) An overview of ensemble methods for binary classifiers in multi-class problems: experimental study on one-vs-one and one-vs-all schemes. Pattern Recognit 44(8):1761\u20131776","journal-title":"Pattern Recognit"},{"issue":"5","key":"4365_CR70","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1109\/PROC.1979.11328","volume":"67","author":"RM Haralick","year":"1979","unstructured":"Haralick RM (1979) Statistical and structural approaches to texture. Proc IEEE 67(5):786\u2013804","journal-title":"Proc IEEE"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04365-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04365-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04365-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,7,24]],"date-time":"2020-07-24T23:21:50Z","timestamp":1595632910000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04365-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,26]]},"references-count":70,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["4365"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04365-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,26]]},"assertion":[{"value":"20 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 July 2019","order":3,"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":"Conflict of interest"}}]}}