{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T10:41:08Z","timestamp":1742380868211,"version":"3.37.3"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,6,26]],"date-time":"2019-06-26T00:00:00Z","timestamp":1561507200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,6,26]],"date-time":"2019-06-26T00:00:00Z","timestamp":1561507200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100007847","name":"Natural Science Foundation of Jilin Province","doi-asserted-by":"publisher","award":["51641609"],"award-info":[{"award-number":["51641609"]}],"id":[{"id":"10.13039\/100007847","id-type":"DOI","asserted-by":"publisher"}]}],"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\/s00521-019-04303-9","type":"journal-article","created":{"date-parts":[[2019,6,27]],"date-time":"2019-06-27T15:03:48Z","timestamp":1561647828000},"page":"8157-8173","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Extreme learning machine with autoencoding receptive fields for image classification"],"prefix":"10.1007","volume":"32","author":[{"given":"Chao","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1032-9910","authenticated-orcid":false,"given":"Yaqian","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhibiao","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,6,26]]},"reference":[{"issue":"16\u201318","key":"4303_CR1","doi-asserted-by":"publisher","first-page":"3056","DOI":"10.1016\/j.neucom.2007.02.009","volume":"70","author":"GB Huang","year":"2007","unstructured":"Huang GB, Chen L (2007) Convex incremental extreme learning machine. Neurocomputing 70(16\u201318):3056\u20133062","journal-title":"Neurocomputing"},{"issue":"16\u201318","key":"4303_CR2","doi-asserted-by":"publisher","first-page":"3460","DOI":"10.1016\/j.neucom.2007.10.008","volume":"71","author":"GB Huang","year":"2008","unstructured":"Huang GB, Chen L (2008) Enhanced random search based incremental extreme learning machine. Neurocomputing 71(16\u201318):3460\u20133468","journal-title":"Neurocomputing"},{"key":"4303_CR3","first-page":"985","volume":"2","author":"GB Huang","year":"2004","unstructured":"Huang GB, Zhu QY, Siew CK (2004) Extreme learning machine: a new learning scheme of feedforward neural networks. Neural Netw 2:985\u2013990","journal-title":"Neural Netw"},{"issue":"1\u20133","key":"4303_CR4","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","volume":"70","author":"GB Huang","year":"2006","unstructured":"Huang GB, Zhu QY, Siew CK (2006) Extreme learning machine: theory and applications. Neurocomputing 70(1\u20133):489\u2013501","journal-title":"Neurocomputing"},{"issue":"2","key":"4303_CR5","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1109\/TSMCB.2011.2168604","volume":"42","author":"GB Huang","year":"2012","unstructured":"Huang GB, Zhou H, Ding X, Zhang R (2012) Extreme learning machine for regression and multiclass classification. IEEE Trans Syst Man Cybern Part B Cybern 42(2):513\u2013529","journal-title":"IEEE Trans Syst Man Cybern Part B Cybern"},{"issue":"2","key":"4303_CR6","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1109\/TPAMI.2016.2545667","volume":"39","author":"P Koniusz","year":"2017","unstructured":"Koniusz P, Yan F, Gosselin PH, Mikolajczyk K (2017) Higher-order occurrence pooling for bags-of-words: visual concept detection. IEEE Trans Pattern Anal Mach Intell 39(2):313\u2013326","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4303_CR7","first-page":"2169","volume":"2","author":"S Lazebnik","year":"2006","unstructured":"Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. IEEE Comput Soc Conf Comput Vis Pattern Recognit 2:2169\u20132178","journal-title":"IEEE Comput Soc Conf Comput Vis Pattern Recognit"},{"key":"4303_CR8","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.neucom.2013.01.057","volume":"128","author":"HG Han","year":"2014","unstructured":"Han HG, Wang LD, Qiao JF (2014) Hierarchical extreme learning machine for feedforward neural network. Neurocomputing 128:128\u2013135","journal-title":"Neurocomputing"},{"issue":"7\u20138","key":"4303_CR9","doi-asserted-by":"publisher","first-page":"1683","DOI":"10.1007\/s00521-013-1398-7","volume":"24","author":"G Li","year":"2014","unstructured":"Li G, Niu P, Duan X, Zhang X (2014) Fast learning network: a novel artificial neural network with a fast learning speed. Neural Comput Appl 24(7\u20138):1683\u20131695","journal-title":"Neural Comput Appl"},{"key":"4303_CR10","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1016\/j.neucom.2015.11.009","volume":"175","author":"BY Qu","year":"2016","unstructured":"Qu BY, Lang B, Liang JJ, Qin AK, Crisalle OD (2016) Two-hidden-layer extreme learning machine for regression and classification. Neurocomputing 175:826\u2013834","journal-title":"Neurocomputing"},{"issue":"2","key":"4303_CR11","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MCI.2015.2405316","volume":"10","author":"GB Huang","year":"2015","unstructured":"Huang GB, Bai Z, Kasun LLC, Vong CM (2015) Local receptive fields based extreme learning machine. IEEE Comput Intell Mag 10(2):18\u201329","journal-title":"IEEE Comput Intell Mag"},{"key":"4303_CR12","first-page":"4700","volume":"2","author":"G Huang","year":"2017","unstructured":"Huang G, Liu Z, Van Der Maaten L, Weinberger KQ (2017) Densely connected convolutional networks. Proc IEEE Conf Comput Vis Pattern Recognit 2:4700\u20134708","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"4303_CR13","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097\u20131105"},{"issue":"2","key":"4303_CR14","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1109\/TII.2016.2605629","volume":"13","author":"H Zhang","year":"2017","unstructured":"Zhang H, Cao X, Ho JK, Chow TW (2017) Object-level video advertising: an optimization framework. IEEE Trans Industr Inf 13(2):520\u2013531","journal-title":"IEEE Trans Industr Inf"},{"key":"4303_CR15","unstructured":"Zhang H, Ji Y, Huang W, Liu L (2018) Sitcom-star-based clothing retrieval for video advertising: a deep learning framework. In: Neural computing and applications, pp 1\u201320"},{"issue":"3","key":"4303_CR16","first-page":"1","volume":"5","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart DE, Hinton GE, Williams RJ (1986) Learning representations by back-propagating errors. Cogn Model 5(3):1","journal-title":"Cogn Model"},{"issue":"8","key":"4303_CR17","doi-asserted-by":"publisher","first-page":"1975","DOI":"10.1007\/s00521-015-2170-y","volume":"28","author":"S Ding","year":"2017","unstructured":"Ding S, Guo L, Hou Y (2017) Extreme learning machine with kernel model based on deep learning. Neural Comput Appl 28(8):1975\u20131984","journal-title":"Neural Comput Appl"},{"key":"4303_CR18","doi-asserted-by":"crossref","unstructured":"Pang S, Yang X (2016) Deep convolutional extreme learning machine and its application in handwritten digit classification. In: Computational intelligence and neuroscience, pp 1\u201310","DOI":"10.1155\/2016\/3049632"},{"key":"4303_CR19","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.neucom.2017.04.077","volume":"277","author":"H Liu","year":"2018","unstructured":"Liu H, Li F, Xu X, Sun F (2018) Multi-modal local receptive field extreme learning machine for object recognition. Neurocomputing 277:4\u201311","journal-title":"Neurocomputing"},{"issue":"3","key":"4303_CR20","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1007\/s11045-016-0414-3","volume":"28","author":"J Huang","year":"2017","unstructured":"Huang J, Yu ZL, Cai Z, Gu Z, Cai Z, Gao W, Yu S, Du Q (2017) Extreme learning machine with multi-scale local receptive fields for texture classification. Multidimens Syst Signal Process 28(3):995\u20131011","journal-title":"Multidimens Syst Signal Process"},{"key":"4303_CR21","unstructured":"He B, Song Y, Zhu Y, Sha Q, Shen Y, Yan T, Nian R, Lendasse A (2018) Local receptive fields based extreme learning machine with hybrid filter kernels for image classification. In: Multidimensional systems and signal processing, pp 1\u201321"},{"issue":"6","key":"4303_CR22","first-page":"31","volume":"28","author":"LLC Kasun","year":"2013","unstructured":"Kasun LLC, Zhou H, Huang GB, Vong CM (2013) Representational learning with extreme learning machine for big data. IEEE Intell Syst 28(6):31\u201334","journal-title":"IEEE Intell Syst"},{"key":"4303_CR23","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"4303_CR24","doi-asserted-by":"crossref","unstructured":"Lu J, Lu Y, Cong G (2011) Reverse spatial and textual k nearest neighbor search. In: Proceedings of the 2011 ACM SIGMOD international conference on management of data. ACM, pp 349\u2013360","DOI":"10.1145\/1989323.1989361"},{"issue":"11","key":"4303_CR25","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":"4303_CR26","doi-asserted-by":"crossref","unstructured":"LeCun Y, Huang FJ, Bottou L (2004) Learning methods for generic object recognition with invariance to pose and lighting. In: Proceedings of the computer vision and pattern recognition, pp 97\u2013104","DOI":"10.1109\/CVPR.2004.1315150"},{"key":"4303_CR27","unstructured":"Krizhevsky A, Hinton G (2009) Learning multiple layers of features from tiny images. Technical report, University of Toronto, vol 1, p 7"},{"key":"4303_CR28","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.neucom.2018.07.050","volume":"316","author":"J Chen","year":"2018","unstructured":"Chen J, Wu Z, Zhang J, Li F, Li W, Wu Z (2018) Cross-covariance regularized autoencoders for nonredundant sparse feature representation. Neurocomputing 316:49\u201358","journal-title":"Neurocomputing"},{"key":"4303_CR29","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1016\/j.neucom.2015.10.035","volume":"174","author":"Y Wang","year":"2016","unstructured":"Wang Y, Xie Z, Xu K, Dou Y, Lei Y (2016) An efficient and effective convolutional auto-encoder extreme learning machine network for 3d feature learning. Neurocomputing 174:988\u2013998","journal-title":"Neurocomputing"},{"key":"4303_CR30","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1016\/j.neucom.2018.05.032","volume":"310","author":"CM Vong","year":"2018","unstructured":"Vong CM, Chen C, Wong PK (2018) Empirical kernel map-based multilayer extreme learning machines for representation learning. Neurocomputing 310:265\u2013276","journal-title":"Neurocomputing"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04303-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04303-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04303-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,6,24]],"date-time":"2020-06-24T23:21:27Z","timestamp":1593040887000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04303-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,26]]},"references-count":30,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["4303"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04303-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2019,6,26]]},"assertion":[{"value":"9 November 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 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 the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}