{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T17:15:07Z","timestamp":1725902107244},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319624099"},{"type":"electronic","value":"9783319624105"}],"license":[{"start":{"date-parts":[[2017,6,21]],"date-time":"2017-06-21T00:00:00Z","timestamp":1498003200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-62410-5_15","type":"book-chapter","created":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T00:23:02Z","timestamp":1497918182000},"page":"124-131","source":"Crossref","is-referenced-by-count":11,"title":["Deep neural networks and transfer learning applied to multimedia web mining"],"prefix":"10.1007","author":[{"given":"Daniel","family":"L\u00f3pez-S\u00e1nchez","sequence":"first","affiliation":[]},{"given":"Ang\u00e9lica Gonz\u00e1lez","family":"Arrieta","sequence":"additional","affiliation":[]},{"given":"Juan M.","family":"Corchado","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,6,21]]},"reference":[{"key":"15_CR1","unstructured":"[1] Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2, 27:1\u201327:27 (2011). Software available at \nhttp:\/\/www.csie.ntu.edu.tw\/~cjlin\/"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"[2] Cortes, C., Vapnik, V.: Support-vector networks. Machine learning 20(3), 273\u2013297 (1995)","DOI":"10.1007\/BF00994018"},{"key":"15_CR3","unstructured":"[3] Fan, R.E., Chang, K.W., Hsieh, C.J., Wang, X.R., Lin, C.J.: LIBLINEAR: A library for large linear classification. Journal of Machine Learning Research 9, 1871\u20131874 (2008)"},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"[4] LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436\u2013444.","DOI":"10.1038\/nature14539"},{"key":"15_CR5","unstructured":"[5] Maaten, L. V. D., & Hinton, G. (2008). Visualizing data using t-SNE. Journal of Machine Learning Research, 9 (Nov), 2579\u20132605."},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"[6] Masoudnia, S., & Ebrahimpour, R. (2014). Mixture of experts: a literature survey. Artificial Intelligence Review, 42(2), 275\u2013293.","DOI":"10.1007\/s10462-012-9338-y"},{"key":"15_CR7","unstructured":"[7] Nair, V. G. (2014). Getting Started with Beautiful Soup. Packt Publishing Ltd."},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"[8] Pan, S. J., & Yang, Q. (2010). A survey on transfer learning. IEEE Transactions on knowledge and data engineering, 22(10), 1345\u20131359.","DOI":"10.1109\/TKDE.2009.191"},{"key":"15_CR9","unstructured":"[9] Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., \u2026 & Vanderplas, J. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12(Oct), 2825\u20132830."},{"key":"15_CR10","doi-asserted-by":"crossref","unstructured":"[10] Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., \u2026 & Berg, A. C. (2015). Imagenet large scale visual recognition challenge. International Journal of Computer Vision, 115(3), 211\u2013252.","DOI":"10.1007\/s11263-015-0816-y"},{"key":"15_CR11","unstructured":"[11] Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint \narXiv:1409.1556\n\n."},{"key":"15_CR12","unstructured":"[12] Yosinski, J., Clune, J., Bengio, Y., & Lipson, H. (2014). How transferable are features in deep neural networks?. In Advances in neural information processing systems (pp. 3320\u20133328)."}],"container-title":["Advances in Intelligent Systems and Computing","Distributed Computing and Artificial Intelligence, 14th International Conference"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-62410-5_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T00:29:32Z","timestamp":1497918572000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-62410-5_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,21]]},"ISBN":["9783319624099","9783319624105"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-62410-5_15","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2017,6,21]]}}}