{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:13:25Z","timestamp":1740158005523,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T00:00:00Z","timestamp":1594252800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T00:00:00Z","timestamp":1594252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100000009","name":"Foundation for the National Institutes of Health","doi-asserted-by":"crossref","award":["R01CA165255","R56DK113819"],"award-info":[{"award-number":["R01CA165255","R56DK113819"]}],"id":[{"id":"10.13039\/100000009","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2020C03098"],"award-info":[{"award-number":["2020C03098"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61601156","61701146","61871164"],"award-info":[{"award-number":["61601156","61701146","61871164"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Universities of Zhejiang Province","award":["GK199900299012-024"],"award-info":[{"award-number":["GK199900299012-024"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s12652-020-02241-2","type":"journal-article","created":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T19:07:46Z","timestamp":1594321666000},"page":"1693-1715","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A hierarchical parallel fusion framework for egocentric ADL recognition based on discernment frame partitioning and belief coarsening"],"prefix":"10.1007","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0900-5276","authenticated-orcid":false,"given":"Haibin","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenyan","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mian","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingui","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,7,9]]},"reference":[{"key":"2241_CR1","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.cviu.2018.05.001","volume":"171","author":"M Aghaei","year":"2018","unstructured":"Aghaei M, Dimiccoli M, Ferrer CC, Radeva P (2018) Towards social pattern characterization in egocentric photo-streams. Comput Vis Image Underst 171:104\u2013117. https:\/\/doi.org\/10.1016\/j.cviu.2018.05.001","journal-title":"Comput Vis Image Underst"},{"key":"2241_CR2","doi-asserted-by":"crossref","unstructured":"Aksasse H, Aksasse B, Ouanan M (2019) Deep convolutional neural networks for human activity classification. In: International conference on information, communication and computing technology (ICICCT 2019), Istanbul City, Turkey, 30\u201331 October, pp 77\u201387","DOI":"10.1007\/978-3-030-38501-9_7"},{"key":"2241_CR3","doi-asserted-by":"publisher","first-page":"31314","DOI":"10.3390\/s151229858","volume":"15","author":"F Attal","year":"2015","unstructured":"Attal F, Mohammed S, Dedabrishvili M, Chamroukhi F, Oukhellou L, Amirat Y (2015) Physical human activity recognition using wearable sensors. Sensors 15:31314\u201331338. https:\/\/doi.org\/10.3390\/s151229858","journal-title":"Sensors"},{"key":"2241_CR4","doi-asserted-by":"publisher","first-page":"37493","DOI":"10.1109\/ACCESS.2018.2850284","volume":"6","author":"S Bano","year":"2018","unstructured":"Bano S, Suveges T, Zhang J, Mckenna SJ (2018) Multimodal egocentric analysis of focused interactions. IEEE Access 6:37493\u201337505. https:\/\/doi.org\/10.1109\/ACCESS.2018.2850284","journal-title":"IEEE Access"},{"key":"2241_CR5","doi-asserted-by":"crossref","unstructured":"Behera A, Hogg DC, Cohn AG (2012) Egocentric activity monitoring and recovery. In: 11th Asian conference on computer vision (ACCV 2012), Daejeon, Korea, November 5\u20139, 2012. Springer, pp 519\u2013532","DOI":"10.1007\/978-3-642-37431-9_40"},{"key":"2241_CR6","doi-asserted-by":"crossref","unstructured":"Cartas A, Luque J, Radeva P, Segura C, Dimiccoli M (2019) Seeing and hearing egocentric actions: how much can we learn? In: The IEEE international conference on computer vision workshop (ICCVW), Seoul, Korea, October 27\u2013November 2, 2019","DOI":"10.1109\/ICCVW.2019.00548"},{"key":"2241_CR7","doi-asserted-by":"publisher","unstructured":"Cartas A, Mar\u00edn J, Radeva P, Dimiccoli M (2017) Recognizing activities of daily living from egocentric images. In: Iberian conference on pattern recognition and image analysis, Faro, Portugal, June 20\u201323, 2017, pp 87\u201395. https:\/\/doi.org\/10.1007\/978-3-319-58838-4_10","DOI":"10.1007\/978-3-319-58838-4_10"},{"key":"2241_CR8","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1007\/s10044-018-0708-1","volume":"21","author":"A Cartas","year":"2018","unstructured":"Cartas A, Mar\u00edn J, Radeva P, Dimiccoli M (2018) Batch-based activity recognition from egocentric photo-streams revisited. Pattern Anal Appl 21:953\u2013965. https:\/\/doi.org\/10.1007\/s10044-018-0708-1","journal-title":"Pattern Anal Appl"},{"key":"2241_CR9","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang CC, Lin CJ (2011) LIBSVM: a library for support vector machines. ACM Trans intel Syst Technol (TIST) 2:27. https:\/\/doi.org\/10.1145\/1961189.1961199","journal-title":"ACM Trans intel Syst Technol (TIST)"},{"key":"2241_CR10","unstructured":"Clarifai Clarifai API. https:\/\/www.clarifai.com\/developer\/. Accessed 25 Feb 2018"},{"key":"2241_CR11","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1109\/JSEN.2016.2628346","volume":"17","author":"M Cornacchia","year":"2017","unstructured":"Cornacchia M, Ozcan K, Zheng Y, Velipasalar S (2017) A survey on activity detection and classification using wearable sensors. IEEE Sens J 17:386\u2013403. https:\/\/doi.org\/10.1109\/JSEN.2016.2628346","journal-title":"IEEE Sens J"},{"key":"2241_CR12","doi-asserted-by":"publisher","first-page":"4119","DOI":"10.3390\/s19194119","volume":"2019","author":"A Diete","year":"2019","unstructured":"Diete A, Stuckenschmidt H (2019) Fusing object information and inertial data for activity recognition. Sensors 2019:4119. https:\/\/doi.org\/10.3390\/s19194119","journal-title":"Sensors"},{"key":"2241_CR13","doi-asserted-by":"publisher","unstructured":"Dimiccoli M, Cartas A, Radeva P (2019) Activity recognition from visual lifelogs: state of the art and future challenges. In: Multimodal behavior analysis in the wild. Elesvier, pp 121\u2013134. https:\/\/doi.org\/10.1016\/B978-0-12-814601-9.00017-1","DOI":"10.1016\/B978-0-12-814601-9.00017-1"},{"key":"2241_CR14","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.trc.2013.09.014","volume":"37","author":"T Feng","year":"2013","unstructured":"Feng T, Timmermans HJP (2013) Transportation mode recognition using GPS and accelerometer data. Transport Res Part C Emerg Technol 37:118\u2013130. https:\/\/doi.org\/10.1016\/j.trc.2013.09.014","journal-title":"Transport Res Part C Emerg Technol"},{"key":"2241_CR15","doi-asserted-by":"crossref","unstructured":"Filios G, Nikoletseas S, Pavlopoulou C, Rapti M, Ziegler S (2015) Hierarchical algorithm for daily activity recognition via smartphone sensors. In: 2015 IEEE 2nd world forum on internet of things (WF-IoT), Milan, Italy, Dec. 14\u201316, 2015, pp 381\u2013386","DOI":"10.1109\/WF-IoT.2015.7389084"},{"key":"2241_CR16","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The elements of statistical learning: data mining, inference, and prediction","author":"T Hastie","year":"2009","unstructured":"Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning: data mining, inference, and prediction. Springer, New York"},{"key":"2241_CR17","doi-asserted-by":"crossref","unstructured":"Hoshen Y, Peleg S (2016) An egocentric look at video photographer identity. In: 2016 IEEE conference on computer vision and pattern recognition (CVPR 2016), Las Vegas, NV, United States, June 27\u201330, 2016. IEEE, pp 4284\u20134292","DOI":"10.1109\/CVPR.2016.464"},{"key":"2241_CR18","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1109\/21.256541","volume":"23","author":"J-SR Jang","year":"1993","unstructured":"Jang J-SR (1993) Anfis: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 23:665\u2013685. https:\/\/doi.org\/10.1109\/21.256541","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"2241_CR19","doi-asserted-by":"publisher","first-page":"1168","DOI":"10.1017\/S1368980018000538","volume":"22","author":"W Jia","year":"2019","unstructured":"Jia W et al (2019) Automatic food detection in egocentric images using artificial intelligence technology. Public Health Nutr 22:1168\u20131179. https:\/\/doi.org\/10.1017\/S1368980018000538","journal-title":"Public Health Nutr"},{"key":"2241_CR20","doi-asserted-by":"crossref","unstructured":"Johnson J, Karpathy A, Fei-Fei L (2016) DenseCap: fully convolutional localization networks for dense captioning. In: 2016 IEEE conference on computer vision and pattern recognition (CVPR 2016), Las Vegas, NV, USA, June 27\u201330, 2016, pp 4565\u20134574","DOI":"10.1109\/CVPR.2016.494"},{"key":"2241_CR21","doi-asserted-by":"crossref","unstructured":"Kapidis G, Poppe R, Dam Ev, Noldus L, Veltkamp R (2019) Multitask learning to improve egocentric action recognition. In: The IEEE international conference on computer vision workshops, Seoul, Korea, 27 October\u20132 November, 2019","DOI":"10.1109\/ICCVW.2019.00540"},{"key":"2241_CR22","doi-asserted-by":"crossref","unstructured":"Kazakos E, Nagrani A, Zisserman A, Damen D (2019) EPIC-fusion: audio-visual temporal binding for egocentric action recognition. In: The IEEE international conference on computer vision (ICCV), Seoul, Korea, October 27\u2013November 2, 2019. pp 5492\u20135501","DOI":"10.1109\/ICCV.2019.00559"},{"key":"2241_CR23","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1109\/TSMC.1985.6313426","volume":"15","author":"JM Keller","year":"1985","unstructured":"Keller JM, Gray MR, Givens JA (1985) A fuzzy K-nearest neighbor algorithm. IEEE Trans Syst Man Cybern 15:580\u2013585. https:\/\/doi.org\/10.1109\/TSMC.1985.6313426","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"2241_CR24","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1016\/j.amepre.2012.11.004","volume":"44","author":"J Kerr","year":"2013","unstructured":"Kerr J et al (2013) Using the SenseCam to improve classifications of sedentary behavior in free-living settings. Am J Prev Med 44:290\u2013296. https:\/\/doi.org\/10.1016\/j.amepre.2012.11.004","journal-title":"Am J Prev Med"},{"key":"2241_CR25","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1145\/1964897.1964918","volume":"12","author":"JR Kwapisz","year":"2011","unstructured":"Kwapisz JR, Weiss GM, Moore SA (2011) Activity recognition using cell phone accelerometers. ACM SIGKDD Explor Newsl 12:74\u201382. https:\/\/doi.org\/10.1145\/1964897.1964918","journal-title":"ACM SIGKDD Explor Newsl"},{"key":"2241_CR26","doi-asserted-by":"publisher","unstructured":"Lakshminarayana NN, Sankaran N, Setlur S, Govindaraju V (2019) Multimodal deep feature aggregation for facial action unit recognition using visible images and physiological signals. In: 2019 14th IEEE international conference on automatic face & gesture recognition (FG 2019), Lille, France, France, 14\u201318 May, 2019. IEEE, pp 1\u20134. https:\/\/doi.org\/10.1109\/FG.2019.8756629","DOI":"10.1109\/FG.2019.8756629"},{"key":"2241_CR27","doi-asserted-by":"publisher","first-page":"1192","DOI":"10.1109\/SURV.2012.110112.00192","volume":"15","author":"OD Lara","year":"2013","unstructured":"Lara OD, Labrador MA (2013) A survey on human activity recognition using wearable sensors. IEEE Commun Surv Tutor 15:1192\u20131209. https:\/\/doi.org\/10.1109\/SURV.2012.110112.00192","journal-title":"IEEE Commun Surv Tutor"},{"key":"2241_CR28","doi-asserted-by":"crossref","unstructured":"Li Y, Ye Z, Rehg JM (2015) Delving into egocentric actions. In: 2015 IEEE conference on computer vision and pattern recognition (CVPR 2015), Boston, MA, USA, June 7\u201312, 2015. IEEE, pp 287\u2013295","DOI":"10.1109\/CVPR.2015.7298625"},{"key":"2241_CR29","unstructured":"Li Z, Wei Z, Jia W, Sun M (2013) Daily life event segmentation for lifestyle evaluation based on multi-sensor data recorded by a wearable device. In: 35th annual international conference of the ieee engineering in medicine and biology society (EMBC 2013), Osaka, Japan, July 3\u20137, 2013. IEEE, pp 2858\u20132861"},{"key":"2241_CR30","doi-asserted-by":"publisher","unstructured":"Oliveira-Barra G, Dimiccoli M, Radeva P (2017) Leveraging activity indexing for egocentric image retrieval. In: Iberian conference on pattern recognition and image analysis, Faro, Portugal, June 20\u201323, 2017. pp 295\u2013303. https:\/\/doi.org\/10.1007\/978-3-319-58838-4_33","DOI":"10.1007\/978-3-319-58838-4_33"},{"key":"2241_CR31","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.ypmed.2010.08.010","volume":"51","author":"M Oliver","year":"2010","unstructured":"Oliver M, Schofield GM, Badland HM, Shepherd J (2010) Utility of accelerometer thresholds for classifying sitting in office workers. Prev Med 51:357\u2013360. https:\/\/doi.org\/10.1016\/j.ypmed.2010.08.010","journal-title":"Prev Med"},{"key":"2241_CR32","first-page":"61","volume":"10","author":"JC Platt","year":"1999","unstructured":"Platt JC (1999) Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Adv Large Margin Classif 10:61\u201374","journal-title":"Adv Large Margin Classif"},{"key":"2241_CR33","doi-asserted-by":"publisher","unstructured":"Possas R, Caceres SP, Ramos F (2018) Egocentric activity recognition on a budget. In: 2018 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), Salt Lake City, UT, USA, 17 December, 2018. IEEE, pp 5967\u20135976. https:\/\/doi.org\/10.1109\/CVPR.2018.00625","DOI":"10.1109\/CVPR.2018.00625"},{"key":"2241_CR34","first-page":"37","volume":"2","author":"DM Powers","year":"2011","unstructured":"Powers DM (2011) Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. J Mach Learn Technol 2:37\u201363","journal-title":"J Mach Learn Technol"},{"key":"2241_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3161174","volume":"1","author":"V Radu","year":"2018","unstructured":"Radu V, Tong C, Bhattacharya S, Lane ND, Mascolo C, Marina MK, Kawsar F (2018) Multimodal deep learning for activity and context recognition. Proc ACM Interact Mobile Wearable Ubiquitous Technol 1:1\u201327. https:\/\/doi.org\/10.1145\/3161174","journal-title":"Proc ACM Interact Mobile Wearable Ubiquitous Technol"},{"key":"2241_CR36","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1145\/361219.361220","volume":"18","author":"G Salton","year":"1975","unstructured":"Salton G, Wong A, Yang CS (1975) A vector space model for automatic indexing. Commun ACM 18:613\u2013620. https:\/\/doi.org\/10.1145\/361219.361220","journal-title":"Commun ACM"},{"key":"2241_CR37","doi-asserted-by":"crossref","DOI":"10.1515\/9780691214696","volume-title":"A mathematical theory of evidence","author":"G Shafer","year":"1976","unstructured":"Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton"},{"key":"2241_CR38","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/0888-613X(90)90012-Q","volume":"4","author":"G Shafer","year":"1990","unstructured":"Shafer G (1990) Perspectives on the theory and practice of belief functions. Int J Approx Reason 4:323\u2013362. https:\/\/doi.org\/10.1016\/0888-613X(90)90012-Q","journal-title":"Int J Approx Reason"},{"key":"2241_CR39","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1016\/0888-613X(87)90024-7","volume":"1","author":"G Shafer","year":"1987","unstructured":"Shafer G, Shenoy PP, Mellouli K (1987) Propagating belief functions in qualitative Markov trees. Int J Approx Reason 1:349\u2013400. https:\/\/doi.org\/10.1016\/0888-613X(87)90024-7","journal-title":"Int J Approx Reason"},{"key":"2241_CR40","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01870-x","author":"L-F Shi","year":"2020","unstructured":"Shi L-F, Qiu C-X, Xin D-J, Liu G-X (2020) Gait recognition via random forests based on wearable inertial measurement unit. J Ambient Intell Humaniz Comput. https:\/\/doi.org\/10.1007\/s12652-020-01870-x","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"2241_CR41","doi-asserted-by":"publisher","unstructured":"Singh S, Arora C, Jawahar CV (2016) First person action recognition using deep learned descriptors. In: 2016 IEEE conference on computer vision and pattern recognition (CVPR), Las Vegas, NV, USA, June 27\u201330, 2016. IEEE, pp 2620\u20132628. https:\/\/doi.org\/10.1109\/CVPR.2016.287","DOI":"10.1109\/CVPR.2016.287"},{"key":"2241_CR42","volume-title":"Advances and applications of DSmT for information fusion","author":"F Smarandache","year":"2004","unstructured":"Smarandache F, Dezert J (2004) Advances and applications of DSmT for information fusion. American Research Press, Rehoboth"},{"key":"2241_CR43","doi-asserted-by":"publisher","unstructured":"Sudhakaran S, Escalera S, Lanz O (2019) LSTA: long short-term attention for egocentric action recognition. In: 2019 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), Long Beach, CA, USA, 15\u201320 June, 2019. IEEE, pp 9954\u20139963. https:\/\/doi.org\/10.1109\/CVPR.2019.01019","DOI":"10.1109\/CVPR.2019.01019"},{"key":"2241_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1260\/2040-2295.6.1.1","volume":"6","author":"M Sun","year":"2015","unstructured":"Sun M et al (2015) An exploratory study on a chest-worn computer for evaluation of diet, physical activity and lifestyle. J Healthc Eng 6:1\u201322. https:\/\/doi.org\/10.1260\/2040-2295.6.1.1","journal-title":"J Healthc Eng"},{"key":"2241_CR45","doi-asserted-by":"crossref","unstructured":"Surie D, Pederson T, Lagriffoul F, Janlert L-E, Sj\u00f6lie D (2007) Activity recognition using an egocentric perspective of everyday objects. In: the 4th international conference on ubiquitous intelligence and computing, Hong Kong, China, July 11\u201313, 2007. Springer, pp 246\u2013257","DOI":"10.1007\/978-3-540-73549-6_25"},{"key":"2241_CR46","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.pmcj.2010.12.001","volume":"8","author":"L Wang","year":"2012","unstructured":"Wang L, Gu T, Tao X, Lu J (2012) A hierarchical approach to real-time activity recognition in body sensor networks. Pervasive Mobile Comput 8:115\u2013130. https:\/\/doi.org\/10.1016\/j.pmcj.2010.12.001","journal-title":"Pervasive Mobile Comput"},{"key":"2241_CR47","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1007\/s12652-016-0395-y","volume":"8","author":"T-H Yang","year":"2017","unstructured":"Yang T-H, Wu C-H, Huang K-Y, Su M-H (2017) Coupled HMM-based Mmultimodal fusion for mood disorder detection through elicited audio\u2013visual signals. J Ambient Intell Humaniz Comput 8:895\u2013906. https:\/\/doi.org\/10.1007\/s12652-016-0395-y","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"2241_CR48","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/s13634-019-0612-x","volume":"14","author":"H Yu","year":"2019","unstructured":"Yu H, Jia W, Li Z, Gong F, Yuan D, Zhang H, Sun M (2019) A multisource fusion framework driven by user-defined knowledge for egocentric activity recognition. EURASIP J Adv Signal Process 14:11\u201323. https:\/\/doi.org\/10.1186\/s13634-019-0612-x","journal-title":"EURASIP J Adv Signal Process"},{"key":"2241_CR49","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.pmcj.2014.11.004","volume":"16","author":"K Zhan","year":"2015","unstructured":"Zhan K, Faux S, Ramos F (2015) Multi-scale conditional random fields for first-person activity recognition on elders and disabled patients. Pervasive Mobile Comput 16:251\u2013267. https:\/\/doi.org\/10.1016\/j.pmcj.2014.11.004","journal-title":"Pervasive Mobile Comput"},{"key":"2241_CR50","doi-asserted-by":"publisher","unstructured":"Zhang W, Huang Y, Yu W, Yang X, Wang W, Sang J (2019) Multimodal attribute and feature embedding for activity recognition. In: ACM multimedia Asia 2019 (MMAsia '19), Beijing, China, 16\u201318 December, 2019. vol 44. pp 1\u20137. https:\/\/doi.org\/10.1145\/3338533.3366592","DOI":"10.1145\/3338533.3366592"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02241-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-020-02241-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02241-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T00:24:12Z","timestamp":1625790252000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-020-02241-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,9]]},"references-count":50,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["2241"],"URL":"https:\/\/doi.org\/10.1007\/s12652-020-02241-2","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"type":"print","value":"1868-5137"},{"type":"electronic","value":"1868-5145"}],"subject":[],"published":{"date-parts":[[2020,7,9]]},"assertion":[{"value":"4 April 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2020","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 there is no conflict of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}