{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T03:45:43Z","timestamp":1775619943836,"version":"3.50.1"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"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":[[2019,5]]},"DOI":"10.1109\/icassp.2019.8683044","type":"proceedings-article","created":{"date-parts":[[2019,4,16]],"date-time":"2019-04-16T20:07:22Z","timestamp":1555445242000},"page":"3842-3846","source":"Crossref","is-referenced-by-count":109,"title":["APE-GAN: Adversarial Perturbation Elimination with GAN"],"prefix":"10.1109","author":[{"given":"Guoqing","family":"Jin","sequence":"first","affiliation":[]},{"given":"Shiwei","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Dongming","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Feng","family":"Dai","sequence":"additional","affiliation":[]},{"given":"Yongdong","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref12","first-page":"2574","article-title":"Deepfool: A simple and accurate method to fool deep neural networks","author":"moosavidezfooli","year":"2016","journal-title":"Computer Vision and Pattern Recognition"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref16","article-title":"Densely connected convolutional networks","author":"huang","year":"2016","journal-title":"Computer Vision and Pattern Recognition"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref19","article-title":"cleverhans v2.0.0: an adversarial machine learning library","author":"goodfellow","year":"2017","journal-title":"arXiv preprint arXiv 1610 09756"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140444"},{"key":"ref3","article-title":"Intriguing properties of neural networks","author":"szegedy","year":"2013","journal-title":"Computer Science"},{"key":"ref6","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"ref8","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"International Conference on Learning Representations"},{"key":"ref7","first-page":"4681","article-title":"Photo-realistic single image super-resolution using a generative adversarial network","author":"ledig","year":"2016","journal-title":"Computer Vision and Pattern Recognition"},{"key":"ref2","article-title":"Adversarial examples in the physical world","author":"kurakin","year":"2016","journal-title":"Computer Vision and Pattern Recognition arXiv"},{"key":"ref1","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2014","journal-title":"Computer Science"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref20","article-title":"Foolbox v0.8.0: A python toolbox to benchmark the robustness of machine learning models","author":"rauber","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref21","article-title":"Technical report on the cleverhans v2.1.0 adversarial examples library","author":"papernot","year":"2018","journal-title":"arXiv preprint arXiv 1610 09756"}],"event":{"name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Brighton, United Kingdom","start":{"date-parts":[[2019,5,12]]},"end":{"date-parts":[[2019,5,17]]}},"container-title":["ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8671773\/8682151\/08683044.pdf?arnumber=8683044","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T03:13:28Z","timestamp":1657854808000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8683044\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/icassp.2019.8683044","relation":{},"subject":[],"published":{"date-parts":[[2019,5]]}}}