{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:09:53Z","timestamp":1775326193159,"version":"3.50.1"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T00:00:00Z","timestamp":1590969600000},"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":[[2020,6]]},"DOI":"10.1109\/comm48946.2020.9142021","type":"proceedings-article","created":{"date-parts":[[2020,7,16]],"date-time":"2020-07-16T20:29:20Z","timestamp":1594931360000},"page":"515-519","source":"Crossref","is-referenced-by-count":13,"title":["CNN Hyperspectral Image Classification Using Training Sample Augmentation with Generative Adversarial Networks"],"prefix":"10.1109","author":[{"given":"Victor-Emil","family":"Neagoe","sequence":"first","affiliation":[]},{"given":"Paul","family":"Diaconescu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2015.7326943"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2015.7326945"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2013.6721339"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8898344"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s41781-017-0004-6"},{"key":"ref15","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"0"},{"key":"ref16","article-title":"Improved techniques for training GANs","author":"salimans","year":"0"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2017.58"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8517955"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518292"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518500"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8519368"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8517816"},{"key":"ref5","first-page":"197","article-title":"A highly configurable deep learning architecture for hyperspectral image classification","author":"diaconescu","year":"0","journal-title":"Proc IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI 2019)"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/rs10020299"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.09.013"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518917"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518956"},{"key":"ref9","article-title":"Generative adversarial nets","author":"goodfellow","year":"0"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8517365"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8519286"},{"key":"ref21","first-page":"5756","article-title":"Can we generate good samples for hyperspectral classification? --A generative adversarial network based method","author":"xu","year":"2028","journal-title":"Proc Int Geoscience Remote Sensing Symp (IGARSS)"}],"event":{"name":"2020 13th International Conference on Communications (COMM)","location":"Bucharest, Romania","start":{"date-parts":[[2020,6,18]]},"end":{"date-parts":[[2020,6,20]]}},"container-title":["2020 13th International Conference on Communications (COMM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9139890\/9141948\/09142021.pdf?arnumber=9142021","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:55:23Z","timestamp":1656345323000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9142021\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/comm48946.2020.9142021","relation":{},"subject":[],"published":{"date-parts":[[2020,6]]}}}