{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T18:32:20Z","timestamp":1771698740448,"version":"3.50.1"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3403457","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T17:28:15Z","timestamp":1716226095000},"page":"73363-73375","source":"Crossref","is-referenced-by-count":2,"title":["SWAG: A Novel Neural Network Architecture Leveraging Polynomial Activation Functions for Enhanced Deep Learning Efficiency"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1836-3075","authenticated-orcid":false,"given":"Saeid","family":"Safaei","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Georgia, Athens, GA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9318-8159","authenticated-orcid":false,"given":"Zerotti","family":"Woods","sequence":"additional","affiliation":[{"name":"Applied Physics Laboratory, Johns Hopkins University, Baltimore, MD, USA"}]},{"given":"Khaled","family":"Rasheed","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Georgia, Athens, GA, USA"}]},{"given":"Thiab R.","family":"Taha","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Georgia, Athens, GA, USA"}]},{"given":"Vahid","family":"Safaei","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, University of Isfahan, Isfahan, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0627-5035","authenticated-orcid":false,"given":"Juan B.","family":"Guti\u00e9rrez","sequence":"additional","affiliation":[{"name":"Department of Mathematics, The University of Texas at San Antonio, San Antonio, TX, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3943-0094","authenticated-orcid":false,"given":"Hamid R.","family":"Arabnia","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Georgia, Athens, GA, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1404.7828"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2016.7727219"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2022.102349"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2020.104103"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/7068349"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2018.2840738"},{"key":"ref8","article-title":"On the selection of initialization and activation function for deep neural networks","author":"Hayou","year":"2018","journal-title":"arXiv:1805.08266"},{"key":"ref9","article-title":"Effectiveness of scaled exponentially-regularized linear units (SERLUs)","author":"Zhang","year":"2018","journal-title":"arXiv:1807.10117"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10955-017-1836-5"},{"issue":"1","key":"ref11","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume-title":"Proc. ICML","volume":"30","author":"Maas"},{"key":"ref12","article-title":"Fast and accurate deep network learning by exponential linear units (ELUs)","author":"Clevert","year":"2015","journal-title":"arXiv:1511.07289"},{"key":"ref13","first-page":"971","article-title":"Self-normalizing neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Klambauer"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/35016072"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459469"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104425"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-24768-5_41"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80131-5"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.U09\/ACCESS.2019.2912200"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106622"},{"issue":"7","key":"ref21","article-title":"Data labeling for supervised learning","volume":"15","author":"Zaveri","year":"2019","journal-title":"PLOS Comput. Biol."},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref23","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330648"},{"key":"ref25","first-page":"1310","article-title":"A review of supervised machine learning algorithms","volume-title":"Proc. 3rd Int. Conf. Comput. Sustain. Global Develop. (INDIACom)","author":"Singh"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.061"},{"key":"ref27","volume-title":"SWAG GitHub Repository","year":"2023"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2019.00209"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00169"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2020.101822"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/72.761726"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/3477.735405"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ITNEC.2016.7560498"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2005.851786"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/3477.537319"},{"key":"ref36","article-title":"Trainable activation function in image classification","author":"Liao","year":"2020","journal-title":"arXiv:2004.13271"},{"key":"ref37","volume-title":"Diabetes","author":"Kahn"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/springerreference_17007"},{"key":"ref39","volume-title":"Connectionist bench (sonar, mines vs. rocks)","author":"Sejnowski"},{"key":"ref40","volume-title":"MNIST Handwritten Digit Database","author":"LeCun","year":"1998"},{"key":"ref41","article-title":"SWAG","author":"Safaei","year":"2023","journal-title":"GitHub repository"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10535176.pdf?arnumber=10535176","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T04:39:25Z","timestamp":1717130365000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10535176\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3403457","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}