{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T08:35:39Z","timestamp":1769675739947,"version":"3.49.0"},"reference-count":63,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Erciyes University Scientific Research Projects Coordination Office","award":["FDK-2025-14627"],"award-info":[{"award-number":["FDK-2025-14627"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2026.3653891","type":"journal-article","created":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T20:59:51Z","timestamp":1768337991000},"page":"8484-8505","source":"Crossref","is-referenced-by-count":0,"title":["ExpAbsTanH: A Novel Activation Function for Image and Video-Based Human Activity Recognition"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7422-5163","authenticated-orcid":false,"given":"Zeynep Vildan","family":"Isik","sequence":"first","affiliation":[{"name":"Department of Computer Programming, Kayseri University, Develi, Kayseri, Türkiye"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3111-5260","authenticated-orcid":false,"given":"Tayyip","family":"Ozcan","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Erciyes University, Melikgazi, Kayseri, Türkiye"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/app13084956"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-024-19711-w"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-025-11388-3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijcce.2024.06.004"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3437371"},{"key":"ref6","article-title":"Action recognition based industrial safety violation detection","author":"Reddy","year":"2024","journal-title":"arXiv:2412.05531"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3353138"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s44196-025-00848-x"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-023-09986-x"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s13735-019-00190-x"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-17748-x"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SACI51354.2021.9465604"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.06.111"},{"key":"ref14","article-title":"Deep learning using rectified linear units (ReLU)","author":"Fred Agarap","year":"2018","journal-title":"arXiv:1803.08375"},{"key":"ref15","article-title":"APALU: A trainable, adaptive activation function for deep learning networks","author":"Subramanian","year":"2024","journal-title":"arXiv:2402.08244"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/BDS\/HPSC\/IDS18.2018.00016"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-5495-7_11"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1134\/S0361768822050036"},{"key":"ref19","article-title":"Three decades of activations: A comprehensive survey of 400 activation functions for neural networks","author":"Kunc","year":"2024","journal-title":"arXiv:2402.09092"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1811.03378"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35289-8_3"},{"key":"ref23","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Statist. (AISTATS)","volume":"9","author":"Glorot"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1710.05941"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ITCA52113.2020.00096"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1908.08681"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.06.067"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11040540"},{"key":"ref29","article-title":"Stable and robust deep learning by hyperbolic tangent exponential linear unit (TeLU)","author":"Fernandez","year":"2024","journal-title":"arXiv:2402.02790"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3373199"},{"issue":"3","key":"ref31","first-page":"261","article-title":"Attention-har: Advanced human activity recognition using a deep learning model with an integrated attention mechanism","volume":"13","author":"Raisi","year":"2025","journal-title":"J. Artif. Intell. Data Min."},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1201\/9781003470939-20"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICDSNS62112.2024.10691103"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2025.104469"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2021.06.045"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref37","author":"LeCun","year":"2010","journal-title":"The MNIST Database of Handwritten Digits"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ESCI50559.2021.9396870"},{"key":"ref39","author":"Krizhevsky","year":"2014","journal-title":"The Cifar-10 Dataset"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/PUNECON.2018.8745428"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-012-0450-4"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1212.0402"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCMC65190.2025.11140675"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-4533-3_31"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/PACRIM61180.2024.10690207"},{"key":"ref46","article-title":"Enhancing fitness movement recognition with attention mechanism and pre-trained feature extractors","author":"Hasan Nishat","year":"2025","journal-title":"arXiv:2509.02511"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3390\/s25092930"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s11265-020-01554-x"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-61068-4_7"},{"key":"ref50","article-title":"Local SGD converges fast and communicates little","author":"Stich","year":"2018","journal-title":"arXiv:1805.09767"},{"key":"ref51","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1049\/cvi2.12020"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104425"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1602.07360"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.17977\/um018v2i12019p41-46"},{"key":"ref56","article-title":"Squashing activation functions in benchmark tests: Towards eXplainable artificial intelligence using continuous-valued logic","author":"Zeltner","year":"2020","journal-title":"arXiv:2010.08760"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.11591\/ijece.v14i1.pp993-1004"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16235"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806222"},{"key":"ref60","article-title":"Optical flow guided feature: A fast and robust motion representation for video action recognition","author":"Sun","year":"2017","journal-title":"arXiv:1711.11152"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.17"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122192"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8846608"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11348121.pdf?arnumber=11348121","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T21:00:47Z","timestamp":1769634047000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11348121\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":63,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3653891","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}