{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:13:36Z","timestamp":1740158016295,"version":"3.37.3"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2022,7,24]],"date-time":"2022-07-24T00:00:00Z","timestamp":1658620800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,24]],"date-time":"2022-07-24T00:00:00Z","timestamp":1658620800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076255"],"award-info":[{"award-number":["62076255"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Science Foundation of Hunan Province","award":["2019JJ20025","2019JJ40406"],"award-info":[{"award-number":["2019JJ20025","2019JJ40406"]}]},{"name":"National Science Foundation of Hunan Province","award":["2021JJ30477"],"award-info":[{"award-number":["2021JJ30477"]}]},{"name":"Research Foundation of Education Bureau of Hunan Province","award":["19B393"],"award-info":[{"award-number":["19B393"]}]},{"name":"Scientific Research Project of Hunan Provincial Department of Education","award":["21B0616"],"award-info":[{"award-number":["21B0616"]}]},{"DOI":"10.13039\/501100012325","name":"National Office for Philosophy and Social Sciences","doi-asserted-by":"publisher","award":["20 &ZD120"],"award-info":[{"award-number":["20 &ZD120"]}],"id":[{"id":"10.13039\/501100012325","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019081","name":"Hunan Provincial Science and Technology Plan Project","doi-asserted-by":"crossref","award":["2020SK2059"],"award-info":[{"award-number":["2020SK2059"]}],"id":[{"id":"10.13039\/501100019081","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Science Foundation of Hunan Province","award":["2022JJ30424"],"award-info":[{"award-number":["2022JJ30424"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s12652-022-04341-7","type":"journal-article","created":{"date-parts":[[2022,7,24]],"date-time":"2022-07-24T20:02:36Z","timestamp":1658692956000},"page":"10657-10671","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["CIOD: an intelligent class-incremental object detection system with nearest mean of exemplars"],"prefix":"10.1007","volume":"14","author":[{"given":"Sheng","family":"Ren","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaokang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4143-6399","authenticated-orcid":false,"given":"Kehua","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Silvio","family":"Barra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqi","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,24]]},"reference":[{"key":"4341_CR1","doi-asserted-by":"publisher","first-page":"149266","DOI":"10.1109\/ACCESS.2021.3124931","volume":"9","author":"MA Al-Asadi","year":"2021","unstructured":"Al-Asadi MA, Tasdem\u00edr S (2021) Empirical comparisons for combining balancing and feature selection strategies for characterizing football players using fifa video game system. IEEE Access 9:149266\u2013149286","journal-title":"IEEE Access"},{"key":"4341_CR2","doi-asserted-by":"publisher","first-page":"22631","DOI":"10.1109\/ACCESS.2022.3154767","volume":"10","author":"MA Al-Asadi","year":"2022","unstructured":"Al-Asadi MA, Tasdem\u0131r S (2022) Predict the value of football players using fifa video game data and machine learning techniques. IEEE Access 10:22631\u201322645","journal-title":"IEEE Access"},{"key":"4341_CR3","doi-asserted-by":"crossref","unstructured":"Al-Waisy AS, Al-Fahdawi S, Mohammed MA et al (2020) Covid-chexnet: hybrid deep learning framework for identifying covid-19 virus in chest x-rays images. Soft Comput:1\u201316","DOI":"10.1007\/s00500-020-05424-3"},{"key":"4341_CR4","doi-asserted-by":"crossref","unstructured":"Carpine F, Mazzariello C, Sansone C (2013) Online irc botnet detection using a soinn classifier. In: 2013 IEEE international conference on communications workshops (ICC), IEEE, pp 1351\u20131356","DOI":"10.1109\/ICCW.2013.6649447"},{"key":"4341_CR5","doi-asserted-by":"crossref","unstructured":"Castro FM, Mar\u00edn-Jim\u00e9nez MJ, Guil N, Schmid C, Alahari K (2018) End-to-end incremental learning. In: Proceedings of the European conference on computer vision (ECCV), pp 233\u2013248","DOI":"10.1007\/978-3-030-01258-8_15"},{"key":"4341_CR6","unstructured":"Ge Z, Liu S, Wang F et al (2021) Yolox: exceeding yolo series in 2021. arXiv preprint arXiv:210708430"},{"key":"4341_CR7","doi-asserted-by":"crossref","unstructured":"Girshick R (2015) Fast r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 1440\u20131448","DOI":"10.1109\/ICCV.2015.169"},{"key":"4341_CR8","doi-asserted-by":"crossref","unstructured":"Girshick R, Donahue J, Darrell T, Malik J (2014) Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 580\u2013587","DOI":"10.1109\/CVPR.2014.81"},{"key":"4341_CR9","doi-asserted-by":"crossref","unstructured":"Gon\u00e7alves GR, Diniz MA, Laroca R, Menotti D, Schwartz WR (2018) Real-time automatic license plate recognition through deep multi-task networks. In: 2018 31st SIBGRAPI conference on graphics. patterns and images (SIBGRAPI), IEEE, pp 110\u2013117","DOI":"10.1109\/SIBGRAPI.2018.00021"},{"key":"4341_CR10","doi-asserted-by":"crossref","unstructured":"Graves A, Mohamed AR, Hinton G (2013) Speech recognition with deep recurrent neural networks. In: 2013 IEEE international conference on acoustics, speech and signal processing, Ieee, pp 6645\u20136649","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"4341_CR11","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.neunet.2015.03.013","volume":"67","author":"B Gu","year":"2015","unstructured":"Gu B, Sheng VS, Wang Z, Ho D, Osman S, Li S (2015) Incremental learning for $\\nu $-support vector regression. Neural Netw 67:140\u2013150","journal-title":"Neural Netw"},{"key":"4341_CR12","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","volume":"187","author":"Y Guo","year":"2016","unstructured":"Guo Y, Liu Y, Oerlemans A, Lao S, Wu S, Lew MS (2016) Deep learning for visual understanding: a review. Neurocomputing 187:27\u201348","journal-title":"Neurocomputing"},{"key":"4341_CR13","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.patrec.2018.10.029","volume":"116","author":"K Guo","year":"2018","unstructured":"Guo K, He Y, Kui X, Sehdev P, Chi T, Zhang R, Li J (2018) Llto: towards efficient lesion localization based on template occlusion strategy in intelligent diagnosis. Pattern Recogn Lett 116:225\u2013232","journal-title":"Pattern Recogn Lett"},{"issue":"1","key":"4341_CR14","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1109\/MSP.2017.2749125","volume":"35","author":"J Han","year":"2018","unstructured":"Han J, Zhang D, Cheng G, Liu N, Xu D (2018) Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Process Mag 35(1):84\u2013100","journal-title":"IEEE Signal Process Mag"},{"key":"4341_CR15","doi-asserted-by":"crossref","unstructured":"He K, Gkioxari G, Doll\u00e1r P, et\u00a0a Girshick R (2017) Mask r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 2961\u20132969","DOI":"10.1109\/ICCV.2017.322"},{"key":"4341_CR16","unstructured":"Kemker R, Kanan C (2017) Fearnet: brain-inspired model for incremental learning. arXiv preprint arXiv:171110563"},{"key":"4341_CR17","doi-asserted-by":"crossref","unstructured":"Kuzborskij I, Orabona F, Caputo B (2013) From n to n+1: multiclass transfer incremental learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3358\u20133365","DOI":"10.1109\/CVPR.2013.431"},{"issue":"11","key":"4341_CR18","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"key":"4341_CR19","doi-asserted-by":"crossref","unstructured":"Lienhart R, Maydt J (2002) An extended set of haar-like features for rapid object detection. In: Proceedings. international conference on image processing, IEEE, pp 900\u2013903","DOI":"10.1109\/ICIP.2002.1038171"},{"key":"4341_CR20","first-page":"21","volume-title":"European conference on computer vision","author":"W Liu","year":"2016","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, Berg AC (2016) Ssd: Single shot multibox detector. European conference on computer vision. Springer, Berlin, pp 21\u201337"},{"key":"4341_CR21","unstructured":"Mohammed M, Azzeddine D, Youssef B, Taoufiq G (2015) Semmdpref: algorithm to filter and sort rules using a semantically based ontology technique. In: Proceedings of the 7th international conference on management of computational and collective intelligence in digital ecosystems, pp 29\u201334"},{"issue":"11","key":"4341_CR22","doi-asserted-by":"publisher","first-page":"3723","DOI":"10.3390\/app10113723","volume":"10","author":"MA Mohammed","year":"2020","unstructured":"Mohammed MA, Abdulkareem KH, Mostafa SA et al (2020) Voice pathology detection and classification using convolutional neural network model. Appl Sci 10(11):3723","journal-title":"Appl Sci"},{"key":"4341_CR23","doi-asserted-by":"crossref","unstructured":"Rebuffi SA, Kolesnikov A, Sperl G, Lampert CH (2017) icarl: incremental classifier and representation learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2001\u20132010","DOI":"10.1109\/CVPR.2017.587"},{"key":"4341_CR24","doi-asserted-by":"crossref","unstructured":"Redmon J, Farhadi A (2017) Yolo9000: better, faster, stronger. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7263\u20137271","DOI":"10.1109\/CVPR.2017.690"},{"key":"4341_CR25","unstructured":"Redmon J, Farhadi A (2018) Yolov3: an incremental improvement. arXiv preprint arXiv:180402767"},{"key":"4341_CR26","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, Farhadi A (2016) You only look once: Unified, real-time object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 779\u2013788","DOI":"10.1109\/CVPR.2016.91"},{"key":"4341_CR27","unstructured":"Ren S, He K, Girshick R, Sun J (2015) Faster r-cnn: towards real-time object detection with region proposal networks. Adv Neural Inf Process Syst 28"},{"key":"4341_CR28","doi-asserted-by":"crossref","unstructured":"Salim FD, Loke SW, Rakotonirainy A, Krishnaswamy S (2007) U &i aware: a framework using data mining and collision detection to increase awareness for intersection users. In: 21st International conference on advanced information networking and applications workshops (AINAW\u201907), IEEE, pp 530\u2013535","DOI":"10.1109\/AINAW.2007.360"},{"issue":"9","key":"4341_CR29","doi-asserted-by":"publisher","first-page":"2022","DOI":"10.1109\/TMM.2017.2699863","volume":"19","author":"F Shen","year":"2017","unstructured":"Shen F, Yang Y, Liu L, Liu W, Tao D, Shen HT (2017) Asymmetric binary coding for image search. IEEE Trans Multimedia 19(9):2022\u20132032","journal-title":"IEEE Trans Multimedia"},{"key":"4341_CR30","unstructured":"Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition. CVPR 2001, Ieee, pp I\u2013I"},{"issue":"3","key":"4341_CR31","doi-asserted-by":"publisher","first-page":"2231","DOI":"10.1109\/TII.2020.2999901","volume":"17","author":"X Wang","year":"2020","unstructured":"Wang X, Yang LT, Song L, Wang H, Ren L, Deen J (2020) A tensor-based multiattributes visual feature recognition method for industrial intelligence. IEEE Trans Ind Inf 17(3):2231\u20132241","journal-title":"IEEE Trans Ind Inf"},{"issue":"3","key":"4341_CR32","doi-asserted-by":"publisher","first-page":"1573","DOI":"10.1109\/TII.2020.2967768","volume":"17","author":"X Wang","year":"2020","unstructured":"Wang X, Yang LT, Wang Y, Ren L, Deen MJ (2020) Adtt: a highly efficient distributed tensor-train decomposition method for iiot big data. IEEE Trans Ind Inf 17(3):1573\u20131582","journal-title":"IEEE Trans Ind Inf"},{"issue":"3","key":"4341_CR33","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1007\/s12652-018-0853-9","volume":"10","author":"Z Wen","year":"2019","unstructured":"Wen Z, Liu D, Liu X, Zhong L, Lv Y, Jia Y (2019) Deep learning based smart radar vision system for object recognition. J Ambient Intell Humaniz Comput 10(3):829\u2013839","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"4341_CR34","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neucom.2015.11.134","volume":"213","author":"W Yang","year":"2016","unstructured":"Yang W, Wang Z, Zhang B (2016) Face recognition using adaptive local ternary patterns method. Neurocomputing 213:183\u2013190","journal-title":"Neurocomputing"},{"issue":"2","key":"4341_CR35","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1109\/TPDS.2017.2754366","volume":"29","author":"L Yu","year":"2017","unstructured":"Yu L, Shen H, Cai Z, Liu L, Pu C (2017) Towards bandwidth guarantee for virtual clusters under demand uncertainty in multi-tenant clouds. IEEE Trans Parallel Distrib Syst 29(2):450\u2013465","journal-title":"IEEE Trans Parallel Distrib Syst"},{"issue":"4","key":"4341_CR36","doi-asserted-by":"publisher","first-page":"1624","DOI":"10.1109\/TITS.2011.2158001","volume":"12","author":"J Zhang","year":"2011","unstructured":"Zhang J, Wang FY, Wang K, Lin WH, Xu X, Chen C (2011) Data-driven intelligent transportation systems: A survey. IEEE Trans Intell Transp Syst 12(4):1624\u20131639","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"4341_CR37","doi-asserted-by":"crossref","unstructured":"Zhang J, Zhang J, Ghosh S, et\u00a0al (2020) Class-incremental learning via deep model consolidation. In: Proceedings of the IEEE\/CVF Winter conference on applications of computer vision, pp 1131\u20131140","DOI":"10.1109\/WACV45572.2020.9093365"},{"issue":"3","key":"4341_CR38","doi-asserted-by":"publisher","first-page":"4854","DOI":"10.1109\/JIOT.2018.2874954","volume":"6","author":"T Zhu","year":"2018","unstructured":"Zhu T, Shi T, Li J, Cai Z, Zhou X (2018) Task scheduling in deadline-aware mobile edge computing systems. IEEE Internet Things J 6(3):4854\u20134866","journal-title":"IEEE Internet Things J"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04341-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-022-04341-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04341-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T15:17:13Z","timestamp":1687360633000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-022-04341-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,24]]},"references-count":38,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["4341"],"URL":"https:\/\/doi.org\/10.1007\/s12652-022-04341-7","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"type":"print","value":"1868-5137"},{"type":"electronic","value":"1868-5145"}],"subject":[],"published":{"date-parts":[[2022,7,24]]},"assertion":[{"value":"22 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Code availability"}}]}}