{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T11:21:17Z","timestamp":1743074477084,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811536847"},{"type":"electronic","value":"9789811536854"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-15-3685-4_12","type":"book-chapter","created":{"date-parts":[[2020,5,20]],"date-time":"2020-05-20T15:19:49Z","timestamp":1589987989000},"page":"325-355","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evolving Deep Neural Networks for X-ray Based Detection of Dangerous Objects"],"prefix":"10.1007","author":[{"given":"Ryotaro","family":"Tsukada","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lekang","family":"Zou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hitoshi","family":"Iba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,21]]},"reference":[{"key":"12_CR1","first-page":"2493","volume":"12","author":"R Collobert","year":"2011","unstructured":"Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12, 2493\u20132537 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"12_CR2","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/TASL.2011.2134090","volume":"20","author":"GE Dahl","year":"2012","unstructured":"Dahl, G.E., Yu, D., Deng, L., Acero, A.: Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition. IEEE Trans. Audio Speech Lang. Process. 20(1), 30\u201342 (2012)","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"12_CR3","unstructured":"Everingham, M., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge 2012 (VOC2012). \nhttp:\/\/host.robots.ox.ac.uk\/pascal\/VOC\/voc2012\/index.html\n\n (2012). Accessed 07 Feb 2019"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"12_CR5","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.: ImageNet classification with deep convolutional neural networks. In: Proceedings of the 25th International Conference on Neural Information Processing Systems (NIPS12), pp.1097\u20131105 (2012)"},{"issue":"11","key":"12_CR6","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.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"12_CR7","unstructured":"Li, Z., Xiong, X., Ren, Z., Zhang, N., Wang, X., Yang, T.: An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints (2018). Preprint arXiv:1806.00851"},{"key":"12_CR8","unstructured":"Maas, A.L., Hannun, A.Y., Ng, A.Y.: Rectifier nonlinearities improve neural network acoustic models. In: Proceedings of International Conference on Machine Learning (ICML), vol. 30, no.1 (2013)"},{"key":"12_CR9","unstructured":"Nie, Y., Iba, H.: evolving convolutional neural network architectures using self-modifying Cartesian genetic programming. Master Thesis, Graduate School of Information Science and Technology, The University of Tokyo, 2019"},{"issue":"10","key":"12_CR10","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345\u20131359 (2010)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"12_CR11","unstructured":"Pham, H., Guan, M.Y., Zoph, B., Le, Q.V., Dean, J.: Efficient Neural Architecture Search via Parameter Sharing (2018). Preprint arXiv: 1802.03268"},{"key":"12_CR12","unstructured":"Redmon, J., Farhadi, A.: YOLO9000: Better, Faster, Stronger (2016). Preprint arXiv: 1612.08242"},{"key":"12_CR13","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You Only Look Once: Unified, Real-Time Object Detection (2015). Preprint arXiv: 1506.02640"},{"key":"12_CR14","first-page":"234","volume-title":"Lecture Notes in Computer Science","author":"Olaf Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: Convolutional Networks for Biomedical Image Segmentation (2015). Preprint arXiv: 1505.04597"},{"issue":"3","key":"12_CR15","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, Z., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 115\u2013211 (2015)","journal-title":"Int. J. Comput. Vis."},{"issue":"2","key":"12_CR16","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1162\/106365602320169811","volume":"10","author":"KO Stanley","year":"2002","unstructured":"Stanley, K.O., Miikkulainen, R.: Evolving neural networks through augmenting topologies. Evol. Comput. 10(2), 99\u2013127 (2002)","journal-title":"Evol. Comput."},{"key":"12_CR17","doi-asserted-by":"crossref","unstructured":"Suganuma, M., Shirakawa, S., Nagao, T.: A genetic programming approach to designing convolutional neural network architectures. In: Proceedings of the Genetic and Evolutionary Computation Conference 2017 (GECCO2017), pp. 497\u2013504 (2017)","DOI":"10.1145\/3071178.3071229"},{"key":"12_CR18","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. In: Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1\u20139 (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"12_CR19","doi-asserted-by":"crossref","unstructured":"Xie, L., Yuille, A.: Genetic CNN. In: Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), pp.1388\u20131397 (2017)","DOI":"10.1109\/ICCV.2017.154"},{"key":"12_CR20","first-page":"714","volume-title":"Security with Intelligent Computing and Big-data Services (SICBS2018). Advances in Intelligent Systems and Computing","author":"L Zou","year":"2019","unstructured":"Zou, L., Tanaka, Y., Iba, H.: Dangerous objects detection of X-ray images using convolution neural network. In: Yang, C.N., Peng, S.L., Jain, L. (eds.) Security with Intelligent Computing and Big-data Services (SICBS2018). Advances in Intelligent Systems and Computing, vol. 895, pp. 714\u2013728. Springer, Cham (2019)"}],"container-title":["Natural Computing Series","Deep Neural Evolution"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-3685-4_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,20]],"date-time":"2020-05-20T15:26:34Z","timestamp":1589988394000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-3685-4_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811536847","9789811536854"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-3685-4_12","relation":{},"ISSN":["1619-7127"],"issn-type":[{"type":"print","value":"1619-7127"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"21 May 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}