{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T20:46:53Z","timestamp":1775854013211,"version":"3.50.1"},"reference-count":37,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"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":[[2020,11]]},"DOI":"10.1109\/sibgrapi51738.2020.00042","type":"proceedings-article","created":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T17:32:11Z","timestamp":1606325531000},"page":"256-263","source":"Crossref","is-referenced-by-count":12,"title":["Packet Vision: a convolutional neural network approach for network traffic classification"],"prefix":"10.1109","author":[{"given":"Rodrigo","family":"Moreira","sequence":"first","affiliation":[{"name":"Institute of Exact and Technological Sciences, Federal University of Viçosa (UFV),Rio Paranaíba\/MG,Brazil"}]},{"given":"Larissa Ferreira","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Institute of Exact and Technological Sciences, Federal University of Viçosa (UFV),Rio Paranaíba\/MG,Brazil"}]},{"given":"Pedro Frosi","family":"Rosa","sequence":"additional","affiliation":[{"name":"Federal University of Uberlândia (UFU),Faculty of Computing (FACOM),Uberlândia\/MG,Brazil"}]},{"given":"Rui L.","family":"Aguiar","sequence":"additional","affiliation":[{"name":"Telecommunications Institute (IT), University of Aveiro,Aveiro,Portugal"}]},{"given":"Fl\u00e1vio de Oliveira","family":"Silva","sequence":"additional","affiliation":[{"name":"Federal University of Uberlândia (UFU),Faculty of Computing (FACOM),Uberlândia\/MG,Brazil"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref32","first-page":"8026","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume":"32","author":"paszke","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref31","author":"duda","year":"2000","journal-title":"Pattern Classification"},{"key":"ref30","author":"devijver","year":"1982","journal-title":"Pattern Recognition a Statistical Approach"},{"key":"ref37","first-page":"2951","article-title":"Practical bayesian optimization of machine learning algorithms","volume":"25","author":"snoek","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref36","first-page":"2546","article-title":"Algorithms for hyper-parameter optimization","volume":"24","author":"bergstra","year":"2011","journal-title":"Advances in neural information processing systems"},{"key":"ref35","first-page":"525","article-title":"Boa: The bayesian optimization algorithm","author":"pelikan","year":"1999","journal-title":"Proceedings of the 1st Annual Conference on Genetic and Evolutionary Computation-Volume 1 GECCO'99"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35289-8_26"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CCBD.2016.029"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1162678.1162679"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107138"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-019-04030-2"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258054"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2019.1800819"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2747560"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE.2019.8861934"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/DSC50466.2020.00048"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.peva.2010.01.001"},{"key":"ref28","article-title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and ¡0.5mb model size","author":"iandola","year":"2016"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103542"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2008.080406"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.07.001"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1091\/mbc.E20-03-0187"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SIBGRAPI-T.2017.12"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.09.116"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/app9122550"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/INDS.2011.6024781"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2872430"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-44041-1_73"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-04918-2_10"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2017.283"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ISCC47284.2019.8969702"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2019.8845315"},{"key":"ref26","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref25","author":"goodfellow","year":"2016","journal-title":"Deep Learning"}],"event":{"name":"2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","location":"Porto de Galinhas, Brazil","start":{"date-parts":[[2020,11,7]]},"end":{"date-parts":[[2020,11,10]]}},"container-title":["2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9265968\/9265969\/09266017.pdf?arnumber=9266017","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T18:13:27Z","timestamp":1754072007000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9266017\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/sibgrapi51738.2020.00042","relation":{},"subject":[],"published":{"date-parts":[[2020,11]]}}}