{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T16:25:05Z","timestamp":1729614305557,"version":"3.28.0"},"reference-count":36,"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.2019.8851911","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":["Generate Desired Images from Trained Generative Adversarial Networks"],"prefix":"10.1109","author":[{"given":"Ming","family":"Li","sequence":"first","affiliation":[]},{"given":"Rui","family":"Xi","sequence":"additional","affiliation":[]},{"given":"Beier","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Mengshu","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Daibo","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Guo","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"ICML"},{"key":"ref32","article-title":"Rectifier nonlinearities improve neural network acoustic models","author":"maas","year":"2013","journal-title":"ICML"},{"key":"ref31","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"ICML"},{"key":"ref30","first-page":"2171","article-title":"Deap: Evolutionary algorithms made easy","volume":"13","author":"fortin","year":"2012","journal-title":"Journal of Machine Learning Research"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1007\/978-3-642-35289-8_25"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref34","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"ICLRE"},{"key":"ref10","first-page":"2172","article-title":"Infogan: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"2016","journal-title":"NIPS"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1038\/scientificamerican0792-66"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/CEC.2009.4983077"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/TEVC.2010.2104157"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1162\/EVCO_a_00025"},{"year":"2017","author":"such","article-title":"Deep neuroevolution: genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning","key":"ref15"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/CVPR.2015.7298640"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/ICCV.2017.629"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref19","first-page":"64","article-title":"Unsupervised learning for physical interaction through video prediction","author":"finn","year":"2016","journal-title":"NIPS"},{"key":"ref28","first-page":"18","volume":"2","author":"lecun","year":"2010","journal-title":"MNIST Handwritten Digit Database"},{"key":"ref4","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"NIPS"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref3","first-page":"1242","article-title":"Deep autoregressive networks","author":"gregor","year":"2014","journal-title":"ICML"},{"key":"ref6","first-page":"1486","article-title":"Deep generative image models using a laplacian pyramid of adversarial networks","author":"denton","year":"2015","journal-title":"NIPS"},{"key":"ref29","article-title":"Pytorch: Tensors and dynamic neural networks in python with strong gpu acceleration","author":"paszke","year":"2017","journal-title":"Pytorch Tensors and Dynamic neural networks in Python with strong GPU acceleration"},{"key":"ref5","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"2016","journal-title":"ICRL"},{"year":"2014","author":"mirza","article-title":"Conditional generative adversarial nets","key":"ref8"},{"key":"ref7","article-title":"Progressive growing of gans for improved quality, stability, and variation","author":"karras","year":"2018","journal-title":"ICLRE"},{"key":"ref2","first-page":"1558","article-title":"Autoencoding beyond pixels using a learned similarity metric","author":"larsen","year":"2016","journal-title":"ICML"},{"key":"ref9","first-page":"2642","article-title":"Conditional image synthesis with auxiliary classifier gans","author":"odena","year":"2017","journal-title":"ICML"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","article-title":"Reducing the dimensionality of data with neural networks","volume":"313","author":"hinton","year":"2006","journal-title":"Science"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref22","first-page":"1857","article-title":"Learning to discover cross-domain relations with generative adversarial networks","author":"kim","year":"2017","journal-title":"ICML"},{"key":"ref21","first-page":"820","article-title":"Dual learning for machine translation","author":"he","year":"2016","journal-title":"NIPS"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/ICCV.2017.244"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/ICCV.2017.310"},{"year":"2017","author":"he","article-title":"Arbitrary facial attribute editing: Only change what you want","key":"ref26"},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v32i1.12277","article-title":"Exprgan: Facial expression editing with controllable expression intensity","author":"ding","year":"2018","journal-title":"AAAI"}],"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\/08851911.pdf?arnumber=8851911","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T16:24:04Z","timestamp":1664555044000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8851911\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2019.8851911","relation":{},"subject":[],"published":{"date-parts":[[2019,7]]}}}