{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:49:05Z","timestamp":1742914145994,"version":"3.40.3"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319168401"},{"type":"electronic","value":"9783319168418"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-16841-8_16","type":"book-chapter","created":{"date-parts":[[2015,4,15]],"date-time":"2015-04-15T02:09:54Z","timestamp":1429063794000},"page":"159-170","source":"Crossref","is-referenced-by-count":0,"title":["Robust and Reliable Feature Extractor Training by Using Unsupervised Pre-training with Self-Organization Map"],"prefix":"10.1007","author":[{"given":"You-Min","family":"Lee","sequence":"first","affiliation":[]},{"given":"Jong-Hwan","family":"Kim","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"1","key":"16_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000006","volume":"2","author":"Y. Bengio","year":"2009","unstructured":"Bengio, Y.: Learning deep architectures for AI. Foundations and Trends\u00ae in Machine Learning\u00a02(1), 1\u2013127 (2009)","journal-title":"Foundations and Trends\u00ae in Machine Learning"},{"key":"16_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1007\/3-540-17943-7_119","volume-title":"PARLE Parallel Architectures and Languages Europe","author":"E.H. Aarts","year":"1987","unstructured":"Aarts, E.H., Jan, H.M.: Boltzmann machines and their applications. In: Treleaven, P.C., Nijman, A.J., de Bakker, J.W. (eds.) PARLE 1987. LNCS, vol.\u00a0258, pp. 34\u201350. Springer, Heidelberg (1987)"},{"issue":"9","key":"16_CR3","doi-asserted-by":"publisher","first-page":"1464","DOI":"10.1109\/5.58325","volume":"78","author":"T. Kohonen","year":"1990","unstructured":"Kohonen, T.: The self-organizing map. Proceedings of the IEEE\u00a078(9), 1464\u20131480 (1990)","journal-title":"Proceedings of the IEEE"},{"key":"16_CR4","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Cognitive Modeling (1988)"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/978-3-642-61068-4_5","volume-title":"Neural Networks","author":"R. Rojas","year":"1996","unstructured":"Rojas, R.: Unsupervised Learning and Clustering Algorithms. In: Neural Networks, pp. 99\u2013121. Springer, Heidelberg (1996)"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Vincent, P., et al.: Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th International Conference on Machine Learning. ACM (2008)","DOI":"10.1145\/1390156.1390294"},{"issue":"1","key":"16_CR7","first-page":"926","volume":"9","author":"G.. Hinton","year":"2010","unstructured":"Hinton, G.: A practical guide to training restricted Boltzmann machines. Momentum\u00a09(1), 926 (2010)","journal-title":"Momentum"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Le, Q.V.: Building high-level features using large scale unsupervised learning. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE (2013)","DOI":"10.1109\/ICASSP.2013.6639343"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Lee, H., et al.: Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In: Proceedings of the 26th Annual International Conference on Machine Learning. ACM (2009)","DOI":"10.1145\/1553374.1553453"},{"issue":"5","key":"16_CR10","doi-asserted-by":"publisher","first-page":"5947","DOI":"10.4249\/scholarpedia.5947","volume":"4","author":"G.E.. Hinton","year":"2009","unstructured":"Hinton, G.E.: Deep belief networks. Scholarpedia\u00a04(5), 5947 (2009)","journal-title":"Scholarpedia"}],"container-title":["Advances in Intelligent Systems and Computing","Robot Intelligence Technology and Applications 3"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-16841-8_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T14:07:05Z","timestamp":1714745225000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-16841-8_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319168401","9783319168418"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-16841-8_16","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2015]]}}}