{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T05:02:31Z","timestamp":1764910951995,"version":"3.46.0"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Image Grap."],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:p>Deep learning has enabled significant advancements in the classification of remote sensing images; however, the task of classifying images in remote sensing remains a formidable challenge because of the high item diversity and complexity that result from spatial and temporal combination and connection. The problem of insufficient differentiation of feature representations generated by deep learning remains, which is mostly due to the similarity and variety of inter-class and intra-class images, respectively. This paper introduces a novel hexagonal network architecture called DenseNet-169, which is based on end-to-end convolutional methods (Bi-LSTM and RNN model) known as CRLSTM-Hexnet. The proposed model comprises three distinct components: (1) a module for extracting features, (2) a feature selection module utilizing the Harris Hawk optimization (HHO) algorithm, and (3) a sub-network based on LSTM and RNN, incorporating a class attention module learning layer. Positive quantitative and qualitative findings from experiments on the RSI-CB256 multi-label dataset confirm the efficacy of our model.<\/jats:p>","DOI":"10.1142\/s021946782650004x","type":"journal-article","created":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T04:04:18Z","timestamp":1719461058000},"source":"Crossref","is-referenced-by-count":1,"title":["CRLSTM-HEXNET: Hybrid Deep Learning Framework with Harris Hawk Optimization in Multi-Label Classification"],"prefix":"10.1142","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5946-2176","authenticated-orcid":false,"given":"Monia","family":"Digra","sequence":"first","affiliation":[{"name":"Department of Computer Science Engineering, Dr. B R Ambedkar National Institute of Engineering and Technology, Punjab, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1641-2619","authenticated-orcid":false,"given":"Renu","family":"Dhir","sequence":"additional","affiliation":[{"name":"Department of Computer Science Engineering, Dr. B R Ambedkar National Institute of Engineering and Technology, Punjab, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3132-3748","authenticated-orcid":false,"given":"Nonita","family":"Sharma","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Indira Gandhi Delhi Technical University for Women, Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2024,6,26]]},"reference":[{"key":"S021946782650004XBIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.10.006"},{"key":"S021946782650004XBIB002","doi-asserted-by":"publisher","DOI":"10.1088\/1755-1315\/113\/1\/012087"},{"key":"S021946782650004XBIB003","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2931801"},{"key":"S021946782650004XBIB004","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2977248"},{"key":"S021946782650004XBIB005","doi-asserted-by":"crossref","unstructured":"G. Cheng, J. Han and X. Lu, \u201cRemote sensing image scene classification: Benchmark and state of the art,\u201d in\n                      Proc. IEEE Inst. Electr. Electron. Eng.\n                      , Vol. 105(10) (2017), pp. 1865\u20131883 (2017), doi:10.1109\/jproc.2017.2675998.","DOI":"10.1109\/JPROC.2017.2675998"},{"issue":"3","key":"S021946782650004XBIB006","first-page":"154","volume":"10","author":"Abbasi H.","year":"2013","journal-title":"Int. J. Comput. Sci. Issues"},{"key":"S021946782650004XBIB007","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.12.015"},{"key":"S021946782650004XBIB008","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3041025"},{"key":"S021946782650004XBIB009","first-page":"1","volume":"60","author":"Cheng G.","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"S021946782650004XBIB010","doi-asserted-by":"publisher","DOI":"10.3390\/rs13142664"},{"key":"S021946782650004XBIB011","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-06912-3"},{"key":"S021946782650004XBIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2017.11.017"},{"key":"S021946782650004XBIB013","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2020.3037893"},{"key":"S021946782650004XBIB014","first-page":"123","volume":"5","author":"Khatriker S.","year":"2018","journal-title":"ISPRS \u2014 Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"S021946782650004XBIB015","doi-asserted-by":"publisher","DOI":"10.1080\/14498596.2017.1345667"},{"key":"S021946782650004XBIB016","first-page":"1","volume":"60","author":"Shamsolmoali P.","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"S021946782650004XBIB017","unstructured":"H. Li\n                      et al.\n                      , \u201cRSI-CB: A large scale remote sensing image classification benchmark via crowdsource data,\u201d arXiv [cs.CV], (2017). [Online]. Available at http:\/\/arXiv.org\/ abs\/1705.10450."},{"key":"S021946782650004XBIB018","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.02.028"},{"key":"S021946782650004XBIB019","doi-asserted-by":"publisher","DOI":"10.1145\/1869790.1869829"},{"key":"S021946782650004XBIB020","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2685945"},{"key":"S021946782650004XBIB021","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2918242"},{"key":"S021946782650004XBIB022","doi-asserted-by":"publisher","DOI":"10.1007\/s12517-022-10246-8"},{"key":"S021946782650004XBIB023","first-page":"298","author":"Xia G.-S.","year":"2010","journal-title":"HAL (Le Centre pour la Communication Scientifique Directe)"},{"key":"S021946782650004XBIB024","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2015.7301382"},{"key":"S021946782650004XBIB025","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2023.01.014"},{"key":"S021946782650004XBIB026","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"S021946782650004XBIB027","first-page":"1","volume":"2013","author":"Olyaee M. H.","year":"2013","journal-title":"J. Soft Comput. Appl."},{"key":"S021946782650004XBIB028","unstructured":"L. Perez and J. Wang, \u201cThe effectiveness of data augmentation in image classification using deep learning,\u201d arXiv [cs.CV], (2017). [Online]. Available at http:\/\/arXiv.org\/abs\/1712.04621."}],"container-title":["International Journal of Image and Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S021946782650004X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T03:20:33Z","timestamp":1764904833000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S021946782650004X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,26]]},"references-count":28,"journal-issue":{"issue":"02","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["10.1142\/S021946782650004X"],"URL":"https:\/\/doi.org\/10.1142\/s021946782650004x","relation":{},"ISSN":["0219-4678","1793-6756"],"issn-type":[{"type":"print","value":"0219-4678"},{"type":"electronic","value":"1793-6756"}],"subject":[],"published":{"date-parts":[[2024,6,26]]},"article-number":"2650004"}}