{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:32:00Z","timestamp":1730266320501,"version":"3.28.0"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1109\/ijcnn.2019.8851684","type":"proceedings-article","created":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T03:44:32Z","timestamp":1569901472000},"page":"1-8","source":"Crossref","is-referenced-by-count":2,"title":["SE-GAN: A Swap Ensemble GAN Framework"],"prefix":"10.1109","author":[{"given":"Licheng","family":"Shen","sequence":"first","affiliation":[]},{"given":"Yan","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"arjovsky","year":"2017","journal-title":"International Conference on Machine Learning"},{"key":"ref11","first-page":"5767","article-title":"Improved training of wasserstein gans","author":"gulrajani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","year":"2015","author":"radford","key":"ref13"},{"article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","year":"2015","author":"ioffe","key":"ref14"},{"key":"ref15","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"Proceedings of the 27th International Conference on Machine Learning (ICML-10)"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"kingma","key":"ref16"},{"article-title":"The MNIST database of handwritten digits","year":"1998","author":"yann","key":"ref17"},{"key":"ref18","first-page":"7","volume":"1","author":"krizhevsky","year":"2009","journal-title":"Learning multiple layers of features from tiny images"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00916"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref6","first-page":"7939","article-title":"Face Aging With Identity-Preserved Conditional Generative Adversarial Networks","author":"wang","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.629"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"article-title":"Image in-painting for irregular holes using partial convolutions","year":"2018","author":"liu","key":"ref7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref1","first-page":"2672","article-title":"Generative Adversarial Nets","author":"goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"article-title":"Towards principled methods for training generative adversarial networks","year":"2017","author":"arjovsky","key":"ref9"},{"article-title":"Boundary-seeking generative adversarial networks","year":"2017","author":"hjelm","key":"ref20"},{"key":"ref22","first-page":"6626","article-title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","author":"heusel","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref21","first-page":"2234","article-title":"Improved techniques for training gans","author":"salimans","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref23","first-page":"698","article-title":"Are gans created equal&#x0192; a large-scale study","author":"lucic","year":"2018","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2019 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2019,7,14]]},"location":"Budapest, Hungary","end":{"date-parts":[[2019,7,19]]}},"container-title":["2019 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8840768\/8851681\/08851684.pdf?arnumber=8851684","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T21:55:28Z","timestamp":1658094928000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8851684\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2019.8851684","relation":{},"subject":[],"published":{"date-parts":[[2019,7]]}}}