{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T09:37:23Z","timestamp":1770284243890,"version":"3.49.0"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030009274","type":"print"},{"value":"9783030009281","type":"electronic"}],"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.springernature.com\/gp\/researchers\/text-and-data-mining"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-00928-1_59","type":"book-chapter","created":{"date-parts":[[2018,9,13]],"date-time":"2018-09-13T03:00:42Z","timestamp":1536807642000},"page":"520-528","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks"],"prefix":"10.1007","author":[{"given":"Hyo-Eun","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seungwook","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jaehwan","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,26]]},"reference":[{"key":"59_CR1","unstructured":"Abadi, M., Agarwal, A., et al.: TensorFlow: large-scale machine learning on heterogeneous systems (2015). http:\/\/tensorflow.org\/"},{"key":"59_CR2","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., et al.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"59_CR3","unstructured":"Goodfellow, I., Pouget-Abadie, J., et al.: Generative adversarial nets. In: NIPS (2014)"},{"key":"59_CR4","unstructured":"Goodfellow, I.J., Mirza, M., et al.: An empirical investigation of catastrophic forgetting in gradient-based neural networks. In: ICLR (2014)"},{"key":"59_CR5","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., et al.: Deep residual learning for image recognition. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"59_CR6","doi-asserted-by":"crossref","unstructured":"Hwang, S., Kim, H.E., et al.: A novel approach for tuberculosis screening based on deep convolutional neural networks. In: SPIE Medical Imaging (2016)","DOI":"10.1117\/12.2216198"},{"key":"59_CR7","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: ICML (2015)"},{"key":"59_CR8","doi-asserted-by":"crossref","unstructured":"Kirkpatrick, J., Pascanu, R., et al.: Overcoming catastrophic forgetting in neural networks. In: PNAS (2017)","DOI":"10.1073\/pnas.1611835114"},{"key":"59_CR9","unstructured":"Krizhevsky, A., Hinton, G.: Learning multiple layers of features from tiny images. In: Technical report, University of Toronto (2009)"},{"key":"59_CR10","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS (2012)"},{"key":"59_CR11","doi-asserted-by":"crossref","unstructured":"Li, Z., Hoiem, D.: Learning without forgetting. In: ECCV (2016)","DOI":"10.1007\/978-3-319-46493-0_37"},{"key":"59_CR12","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/S0079-7421(08)60536-8","volume":"24","author":"M McCloskey","year":"1989","unstructured":"McCloskey, M., Cohen, N.J.: Catastrophic interference in connectionist networks: the sequential learning problem. Psychol. Learn. Motiv. 24, 109\u2013165 (1989)","journal-title":"Psychol. Learn. Motiv."},{"key":"59_CR13","unstructured":"Shin, H., Lee, J.K., et al.: Continual learning with deep generative replay (2017). arXiv:1705.08690"},{"key":"59_CR14","first-page":"3371","volume":"11","author":"P Vincent","year":"2010","unstructured":"Vincent, P., Larochelle, H.: Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. JMLR 11, 3371\u20133408 (2010)","journal-title":"JMLR"},{"key":"59_CR15","unstructured":"Wu, Y., Schuster, M., et al.: Google\u2019s neural machine translation system: Bridging the gap between human and machine translation (2016)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00928-1_59","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T00:33:07Z","timestamp":1694565187000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00928-1_59"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030009274","9783030009281"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00928-1_59","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"26 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","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":"16 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}