{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T11:59:43Z","timestamp":1773748783717,"version":"3.50.1"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-026-21464-7","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T11:02:40Z","timestamp":1773745360000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modeling an enhanced Mayfly optimizer algorithm integrated with deep convolutional neural networks for accurate scene classification in remote sensing imagery"],"prefix":"10.1007","volume":"85","author":[{"given":"M.","family":"Rega","sequence":"first","affiliation":[]},{"given":"S.","family":"Sivakumar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,17]]},"reference":[{"key":"21464_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rsase.2023.101126","volume":"33","author":"A Sivasubramanian","year":"2024","unstructured":"Sivasubramanian A, Prashanth VR, Hari T, Sowmya V, Gopalakrishnan EA, Ravi V (2024) Transformer-based convolutional neural network approach for remote sensing natural scene classification. Remote Sensing Applications: Society and Environment 33:101126","journal-title":"Remote Sensing Applications: Society and Environment"},{"issue":"22","key":"21464_CR2","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11223727","volume":"11","author":"Z Chen","year":"2022","unstructured":"Chen Z, Yang J, Feng Z, Chen L (2022) RSCNet: an efficient remote sensing scene classification model based on lightweight convolution neural networks. Electronics 11(22):3727","journal-title":"Electronics"},{"issue":"4","key":"21464_CR3","first-page":"34","volume":"6","author":"V Karthick","year":"2023","unstructured":"Karthick V, Aiswarya MC, Jayavarshini GR, Sruthi R (2023) Remote sensing scene classification using convolutional neural network. Int J Res Eng Sci Manage 6(4):34\u201338","journal-title":"Int J Res Eng Sci Manage"},{"issue":"3","key":"21464_CR4","doi-asserted-by":"publisher","DOI":"10.3390\/electronics13030583","volume":"13","author":"CC Yu","year":"2024","unstructured":"Yu CC, Chen TY, Hsu CW, Cheng HY (2024) Incremental scene classification using dual knowledge distillation and classifier discrepancy on natural and remote sensing images. Electronics 13(3):583","journal-title":"Electronics"},{"issue":"2","key":"21464_CR5","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/s10707-023-00492-7","volume":"27","author":"MI Siddiqui","year":"2023","unstructured":"Siddiqui MI, Khan K, Fazil A, Zakwan M (2023) Snapshot ensemble-based residual network (SnapEnsemResNet) for remote sensing image scene classification. GeoInformatica 27(2):341\u2013372","journal-title":"GeoInformatica"},{"issue":"13","key":"21464_CR6","doi-asserted-by":"publisher","DOI":"10.3390\/rs14133184","volume":"14","author":"C Shi","year":"2022","unstructured":"Shi C, Zhang X, Wang T, Wang L (2022) A lightweight convolutional neural network based on hierarchical-wise convolution fusion for remote-sensing scene image classification. Remote Sens 14(13):3184","journal-title":"Remote Sens"},{"issue":"3","key":"21464_CR7","doi-asserted-by":"publisher","DOI":"10.3390\/rs16030525","volume":"16","author":"Z Dong","year":"2024","unstructured":"Dong Z, Lin B, Xie F (2024) Optimising few-shot remote sensing scene classification based on an improved data augmentation approach. Remote Sens 16(3):525","journal-title":"Remote Sens"},{"key":"21464_CR8","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2023.3304645","author":"YE Hou","year":"2023","unstructured":"Hou YE, Yang K, Dang L, Liu Y (2023) Contextual spatial-channel attention network for remote sensing scene classification. IEEE Geosci Remote Sens Lett. https:\/\/doi.org\/10.1109\/LGRS.2023.3304645","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"21464_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2024.3359415","author":"D Li","year":"2024","unstructured":"Li D, Liu R, Tang Y, Liu Y (2024) PSCLI-TF: position-sensitive cross-layer interactive transformer model for remote sensing image scene classification. IEEE Geosci Remote Sens Lett. https:\/\/doi.org\/10.1109\/LGRS.2024.3359415","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"21464_CR10","first-page":"1","volume":"61","author":"Y Zhao","year":"2023","unstructured":"Zhao Y, Liu J, Yang J, Wu Z (2023) EMSCNet: efficient multisample contrastive network for remote sensing image scene classification. IEEE Trans Geosci Remote Sens 61:1\u201314","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"21464_CR11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3348464","author":"F Tian","year":"2024","unstructured":"Tian F, Lei S, Zhou Y, Cheng J, Liang G, Zou Z, Li HC, Shi Z (2024) HiReNet: hierarchical-relation network for few-shot remote sensing image scene classification. IEEE Trans Geosci Remote Sens. https:\/\/doi.org\/10.1109\/TGRS.2023.3348464","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"3","key":"21464_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/rs14030545","volume":"14","author":"C Shi","year":"2022","unstructured":"Shi C, Zhang X, Sun J, Wang L (2022) Remote sensing scene image classification based on self-compensating convolution neural network. Remote Sens 14(3):545","journal-title":"Remote Sens"},{"issue":"21","key":"21464_CR13","doi-asserted-by":"publisher","first-page":"6615","DOI":"10.1080\/01431161.2023.2273246","volume":"44","author":"C Shi","year":"2023","unstructured":"Shi C, Zhang X, Wang L, Jin Z (2023) A lightweight convolution neural network based on joint features for remote sensing scene image classification. Int J Remote Sens 44(21):6615\u20136641","journal-title":"Int J Remote Sens"},{"key":"21464_CR14","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2024.3353796","author":"K Zhang","year":"2024","unstructured":"Zhang K, Cui T, Wu W, Zheng X, Cheng G (2024) Large kernel separable mixed ConvNet for remote sensing scene classification. IEEE J Sel Top Appl Earth Obs Remote Sens. https:\/\/doi.org\/10.1109\/JSTARS.2024.3353796","journal-title":"IEEE J Sel Top Appl Earth Obs Remote Sens"},{"key":"21464_CR15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3306083","author":"L Wei","year":"2023","unstructured":"Wei L, Geng C, Yin Y (2023) Remote sensing image scene classification based on head-tail global joint dual attention discrimination network. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2023.3306083","journal-title":"IEEE Access"},{"key":"21464_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.107909","volume":"132","author":"H Yue","year":"2024","unstructured":"Yue H, Qing L, Zhang Z, Wang Z, Guo L, Peng Y (2024) MSE-net: a novel master\u2013slave encoding network for remote sensing scene classification. Eng Appl Artif Intell 132:107909","journal-title":"Eng Appl Artif Intell"},{"issue":"23","key":"21464_CR17","doi-asserted-by":"publisher","DOI":"10.3390\/rs15235620","volume":"15","author":"C Shi","year":"2023","unstructured":"Shi C, Ding M, Wang L, Pan H (2023) Learn by yourself: a feature-augmented self-distillation convolutional neural network for remote sensing scene image classification. Remote Sens 15(23):5620","journal-title":"Remote Sens"},{"key":"21464_CR18","doi-asserted-by":"crossref","unstructured":"Sheer AH, Al-Ani AA (2018) November. The effect of regularisation parameter within non-blind restoration algorithm using modified iterative wiener filter for medical image. In 2018 1st Annual International Conference on Information and Sciences (AiCIS) (pp. 77\u201381). IEEE","DOI":"10.1109\/AiCIS.2018.00026"},{"issue":"2","key":"21464_CR19","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1080\/00051144.2023.2295142","volume":"65","author":"A Sanampudi","year":"2024","unstructured":"Sanampudi A, Srinivasan S (2024) Local search enhanced optimal Inception-ResNet-v2 for classification of long-term lung diseases in post-COVID-19 patients. Automatika 65(2):473\u2013482","journal-title":"Automatika"},{"issue":"13","key":"21464_CR20","doi-asserted-by":"publisher","DOI":"10.3390\/app13137833","volume":"13","author":"N Alqahtani","year":"2023","unstructured":"Alqahtani N, Alam S, Aqeel I, Shuaib M, Mohsen Khormi I, Khan SB, Malibari AA (2023) Deep belief networks (DBN) with IoT-based Alzheimer\u2019s disease detection and classification. Appl Sci 13(13):7833","journal-title":"Appl Sci"},{"issue":"1\u20132","key":"21464_CR21","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1177\/00202940221088713","volume":"56","author":"Y Yan","year":"2023","unstructured":"Yan Y, Hu Z, Yuan W, Wang J (2023) Pipeline leak detection based on empirical mode decomposition and deep belief network. Meas Control 56(1\u20132):396\u2013402","journal-title":"Meas Control"},{"key":"21464_CR22","unstructured":"http:\/\/weegee.vision.ucmerced.edu\/datasets\/landuse.html"},{"key":"21464_CR23","unstructured":"https:\/\/captain-whu.github.io\/AID\/"},{"issue":"19","key":"21464_CR24","doi-asserted-by":"publisher","DOI":"10.3390\/rs14194813","volume":"14","author":"Y Zhao","year":"2022","unstructured":"Zhao Y, Liu J, Yang J, Wu Z (2022) Remote sensing image scene classification via self-supervised learning and knowledge distillation. Remote Sens 14(19):4813","journal-title":"Remote Sens"},{"key":"21464_CR25","doi-asserted-by":"publisher","first-page":"135383","DOI":"10.1109\/ACCESS.2020.3011502","volume":"8","author":"A Rajagopal","year":"2020","unstructured":"Rajagopal A, Joshi GP, Ramachandran A, Subhalakshmi RT, Khari M, Jha S, Shankar K, You J (2020) A deep learning model based on multi-objective particle swarm optimisation for scene classification in unmanned aerial vehicles. IEEE Access 8:135383\u2013135393","journal-title":"IEEE Access"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-026-21464-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-026-21464-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-026-21464-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T11:02:42Z","timestamp":1773745362000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-026-21464-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,17]]},"references-count":25,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["21464"],"URL":"https:\/\/doi.org\/10.1007\/s11042-026-21464-7","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,17]]},"assertion":[{"value":"28 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 February 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 February 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 March 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No ethics approval is required.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"Not Applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"Not Applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human And Animal Ethics"}},{"value":"The authors declare that we have no competing interest.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"283"}}