{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T19:09:23Z","timestamp":1759777763820,"version":"3.41.0"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319917962"},{"type":"electronic","value":"9783319917979"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-91797-9_55","type":"book-chapter","created":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T11:12:48Z","timestamp":1527851568000},"page":"795-806","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Deep Learning Model and Its Application in Big Data"],"prefix":"10.1007","author":[{"given":"Yuanming","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Shifeng","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Xuesong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,2]]},"reference":[{"key":"55_CR1","unstructured":"Yu, B., Li, S., et al.: Deep learning: a key of stepping into the era of big data. J. Eng. Stud. 20\u201345 (2014)"},{"key":"55_CR2","doi-asserted-by":"crossref","unstructured":"Wu, M., Chen, L.: Image recognition based on deep learning. In: Chinese Automation Congress, Wuhan, China, pp. 542\u2013546 (2015)","DOI":"10.1109\/CAC.2015.7382560"},{"key":"55_CR3","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Xu, Y.M., Sun, M.J., et al.: Cross-language transfer speech recognition using deep learning. In: Proceedings of the 11th IEEE International Conference of Control & Automation (ICCA), Munich, Germany, pp. 1422\u20131426 (2014)","DOI":"10.1109\/ICCA.2014.6871132"},{"key":"55_CR4","first-page":"005","volume":"1","author":"J Wang","year":"2017","unstructured":"Wang, J., Chen, H., Liu, Q.: The study of deep learning under big data. Chin. High Technol. Lett. 1, 005 (2017)","journal-title":"Chin. High Technol. Lett."},{"issue":"7","key":"55_CR5","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Ten, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"key":"55_CR6","doi-asserted-by":"crossref","unstructured":"Bengio, Y., Lamblin, P., Popovici, D., et al.: Greedy layer-wise training of deep networks. In: Advances in Neural Information Processing Systems, pp. 153\u2013160. MIT Press, Cambridge (2007)","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"55_CR7","doi-asserted-by":"crossref","unstructured":"Zeiler, M.D., Krishnan, D., Taylor, G.W., et al.: Deconvolutional networks. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2528\u20132535. IEEE, Piscataway (2010)","DOI":"10.1109\/CVPR.2010.5539957"},{"issue":"4","key":"55_CR8","first-page":"23","volume":"53","author":"GVR Sagar","year":"2012","unstructured":"Sagar, G.V.R., Venkata, C.S.: Simultaneous evolution of architecture and connection weights in artificial neural network. Int. J. Comput. Appl. 53(4), 23\u201328 (2012)","journal-title":"Int. J. Comput. Appl."},{"key":"55_CR9","doi-asserted-by":"crossref","unstructured":"Zen, H., Senior, A., Schuster, M.: Statistical parametric speech synthesis using deep neural networks. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7962\u20137966. IEEE, Piscataway (2013)","DOI":"10.1109\/ICASSP.2013.6639215"},{"key":"55_CR10","doi-asserted-by":"crossref","unstructured":"Tokuda, K., Yoshimura, T., Masuko, T., et al.: Speech parameter generation algorithms for HMM-based speech synthesis. In: Proceedings of 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 1315\u20131318. IEEE, Piscataway (2000)","DOI":"10.1109\/ICASSP.2000.861820"},{"key":"55_CR11","unstructured":"Cheng, Z.: Research and Application of Large Scale Multi-layer Perceptron Neural Network Jilin University, vol. 6 (2017)"},{"key":"55_CR12","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1007\/978-3-319-27857-5_77","volume-title":"Advances in Visual Computing","author":"Adam W. Harley","year":"2015","unstructured":"Harley, A.W.: An interactive node-link visualization of convolutional neural networks. In: ISVC, pp. 867\u2013877 (2015)"},{"issue":"9","key":"55_CR13","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"K He","year":"2014","unstructured":"He, K., Zhang, X., Ren, S., et al.: Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1904\u20131916 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"55_CR14","doi-asserted-by":"crossref","unstructured":"Simard, P., Steinkraus, D., Platt, J.C.: Best practices for convolutional neural networks applied to visual document analysis. In: Seventh International Conference on Document Analysis and Recognition (ICDAR 2003), vol. 2, pp. 958\u2013962. IEEE (2003)","DOI":"10.1109\/ICDAR.2003.1227801"},{"issue":"11","key":"55_CR15","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y Lecun","year":"1998","unstructured":"Lecun, Y., BottouL, B.Y., et al.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"55_CR16","unstructured":"Sun, J., He, K.M., Zhang, X.Y., et al.: Delving deep into rectifiers: surpassing human-level performance on imagenet classification (2015)"},{"key":"55_CR17","doi-asserted-by":"crossref","unstructured":"Satish, N., Sundaram, N., Keutzer, K.: Optimizing the use of GPU memory in applications with large data sets. In: Proceedings of the 16th International Conference on High Performance Computing, Kochi, India, pp. 408\u2013418 (2009)","DOI":"10.1109\/HIPC.2009.5433185"},{"key":"55_CR18","doi-asserted-by":"crossref","unstructured":"Bengio, Y., Lamblin, P., Popovici, D., et al.: Greedy layer-wise training of deep networks. In: Advances in Neural Information Processing Systems 19, p. 153. Neural Information Processing Systems Foundation, Inc. (2006)","DOI":"10.7551\/mitpress\/7503.003.0024"},{"key":"55_CR19","doi-asserted-by":"crossref","unstructured":"Sak, H., Senior, A., Beaufays, F.: Long short-term memory recurrent neural network architectures for large scale acoustic modeling. In: 15th Annual Conference of the International Speech Communication Association (Interspeech 2014), Singapore, pp. 338\u2013342 (2014)","DOI":"10.21437\/Interspeech.2014-80"},{"key":"55_CR20","unstructured":"Zhang, G., Zhang, P.Y., Pan, J., et al.: Fast decoding algorithm for automatic speech recognition based on recurrent neural networks. J. Electron. Inf. Technol. 4 (2017)"},{"key":"55_CR21","unstructured":"Yosuke, O., Akihiro, N.: Predicting statistics of asynchronous SGD parameters for a large-scale distributed deep learning system on GPU supercomputers, pp. 306\u2013331 (2016)"},{"key":"55_CR22","unstructured":"Noam, S., Azalia, M., Krzysztof, M., et al.: Outrageously large neural networks: the sparsely-gated mixture-of-experts layer, pp. 204\u2013220 (2017)"},{"issue":"12","key":"55_CR23","doi-asserted-by":"publisher","first-page":"3207","DOI":"10.1162\/NECO_a_00052","volume":"22","author":"DC Ciresan","year":"2010","unstructured":"Ciresan, D.C., Meier, U., Gamarde lla, L.M., et al.: Deep, big, simple neural nets for handwritten digit recognition. Neural Comput. 22(12), 3207\u20133220 (2010)","journal-title":"Neural Comput."},{"key":"55_CR24","unstructured":"Ranzato, M., Poultney, C., Chopra, S., et al.: Efficient learning of sparse representations with an energy-based model. In: Advances in Neural Information Processing Systems Foundations, Inc., pp. 379\u2013420 (2006)"},{"key":"55_CR25","unstructured":"Dzmitry, B.,Yoshua, B.: Neural machine translation by jointly learning to align translate. Published as a Conference Paper at ICLR 2015, pp. 167\u2013190 (2015)"},{"key":"55_CR26","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1038\/nature24270","volume":"550","author":"S David","year":"2017","unstructured":"David, S., Julian, S., Karen, S., et al.: Mastering the game of go without human knowledge. Nature 550, 354\u2013359 (2017)","journal-title":"Nature"}],"container-title":["Lecture Notes in Computer Science","Design, User Experience, and Usability: Theory and Practice"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-91797-9_55","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T22:57:05Z","timestamp":1751669825000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-91797-9_55"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319917962","9783319917979"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-91797-9_55","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"2 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DUXU","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of Design, User Experience, and Usability","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Las Vegas, NV","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 July 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 July 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"duxu2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2018.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}