{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T09:24:23Z","timestamp":1767000263306,"version":"3.48.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T00:00:00Z","timestamp":1766966400000},"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":["SN COMPUT. SCI."],"DOI":"10.1007\/s42979-025-04645-3","type":"journal-article","created":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T09:21:32Z","timestamp":1767000092000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Performance Analysis of Shallow Convolutional Neural Network-Based Hybrid Model for Image Classification"],"prefix":"10.1007","volume":"7","author":[{"given":"Arman Ahmed","family":"Shawon","sequence":"first","affiliation":[]},{"given":"Fatema Jannat","family":"Dihan","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Qiao","sequence":"additional","affiliation":[]},{"given":"Md. Bipul","family":"Hossain","sequence":"additional","affiliation":[]},{"given":"Saydul Akbar","family":"Murad","sequence":"additional","affiliation":[]},{"given":"Mahadi","family":"Hasan","sequence":"additional","affiliation":[]},{"given":"Luyao","family":"Zou","sequence":"additional","affiliation":[]},{"given":"Monishanker","family":"Halder","sequence":"additional","affiliation":[]},{"given":"Avi Deb","family":"Raha","sequence":"additional","affiliation":[]},{"given":"Mrityunjoy","family":"Gain","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3970-1878","authenticated-orcid":false,"given":"Apurba","family":"Adhikary","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,29]]},"reference":[{"issue":"4","key":"4645_CR1","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1111\/dgd.12054","volume":"55","author":"S Uchida","year":"2013","unstructured":"Uchida S. Image processing and recognition for biological images. Dev Growth Differ. 2013;55(4):523\u201349.","journal-title":"Dev Growth Differ"},{"key":"4645_CR2","unstructured":"Wu R, Yan S, Shan Y, Dang Q, Sun G. Deep image: scaling up image recognition. 2015;7(8):4. arXiv preprint arXiv:1501.02876"},{"key":"4645_CR3","doi-asserted-by":"crossref","unstructured":"Hossain MB, Shama A, Adhikary A, Raha AD, Uddin KA, Hossain MA, Islam I, Murad SA, Munir MS, Bairagi AK. An explainable artificial intelligence framework for the predictive analysis of hypo and hyper thyroidism using machine learning algorithms. Human-Centric Intell Syst. 2023:1\u201321","DOI":"10.1007\/s44230-023-00027-1"},{"issue":"4","key":"4645_CR4","first-page":"563","volume":"12","author":"MA Abu","year":"2019","unstructured":"Abu MA, Indra NH, Rahman A, Sapiee NA, Ahmad I. A study on image classification based on deep learning and tensorflow. Int J Eng Res Technol. 2019;12(4):563\u20139.","journal-title":"Int J Eng Res Technol"},{"key":"4645_CR5","doi-asserted-by":"crossref","unstructured":"Penchala S, Murad SA, Roy I, Gupta B, Rahimi N. Unveiling text mining potential: a comparative analysis of document classification algorithms. In: Proceedings of 39th international conference 2024;98:103\u201315.","DOI":"10.29007\/lsgw"},{"issue":"5","key":"4645_CR6","doi-asserted-by":"publisher","first-page":"441","DOI":"10.5626\/JOK.2023.50.5.441","volume":"50","author":"A Apurba","year":"2023","unstructured":"Apurba A, Shirajum MM, Deb RA, Seok KM, Won CJ, Seon HC. A deep learning approach for target-oriented communication resource allocation in holographic mimo. J KIISE. 2023;50(5):441\u201350.","journal-title":"J KIISE"},{"key":"4645_CR7","first-page":"201","volume":"5","author":"S Pratt","year":"2021","unstructured":"Pratt S. From the eyes of a machine: image recognition technologies. Geo Law Tech Rev. 2021;5:201.","journal-title":"Geo Law Tech Rev"},{"key":"4645_CR8","doi-asserted-by":"crossref","unstructured":"Murad SA, Rahimi N, Muzahid AJM. Phishguard: machine learning-powered phishing url detection. In: 2023 congress in computer science, computer engineering, and applied computing (CSCE), 2023:2279\u201384, IEEE.","DOI":"10.1109\/CSCE60160.2023.00371"},{"key":"4645_CR9","doi-asserted-by":"crossref","unstructured":"Makbul NE, Zannat R, Hale BJ. Communicating sex work online: a content analysis of client and provider discourse in r\/sexworkers. J Sex Res. 2023:1\u201312","DOI":"10.1080\/00224499.2023.2255180"},{"key":"4645_CR10","doi-asserted-by":"crossref","unstructured":"Apurba A, Shirajum MM, Deb RA, Yu Q, Seon HC. Artificial intelligence framework for target oriented integrated sensing and communication in holographic mimo. In: NOMS 2023-2023 IEEE\/IFIP network operations and management symposium, 2023:1\u20137, IEEE.","DOI":"10.1109\/NOMS56928.2023.10154354"},{"key":"4645_CR11","unstructured":"Apurba A, Shirajum MM, Deb RA, Yu Q, Zhu H, Seon HC. Integrated sensing, localization, and communication in holographic mimo-enabled wireless network: a deep learning approach. IEEE Trans Network Serv Manag. 10\u2013110920233292269 2023."},{"issue":"1\u20132","key":"4645_CR12","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1163\/22142312-12340101","volume":"6","author":"N Uddin","year":"2019","unstructured":"Uddin N, Faisal HM, Zannat R. Solar energy for ict advancement: an empirical study on coastal areas in Bangladesh. Asiascape Dig Asia. 2019;6(1\u20132):35\u201357.","journal-title":"Asiascape Dig Asia"},{"key":"4645_CR13","doi-asserted-by":"crossref","unstructured":"Rahman M, Debnath S, Rana M, Murad SA, Muzahid AJM, Rashid SZ, Gafur A. Bangla text summarization analysis using machine learning: an extractive approach. In: International human engineering symposium, 2023:65\u201380, Springer.","DOI":"10.1007\/978-981-99-6890-9_6"},{"key":"4645_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105728","volume":"178","author":"LB Ferreira","year":"2020","unstructured":"Ferreira LB, da Cunha FF. Multi-step ahead forecasting of daily reference evapotranspiration using deep learning. Comput Electron Agric. 2020;178:105728.","journal-title":"Comput Electron Agric"},{"key":"4645_CR15","unstructured":"Agarap AF. An architecture combining convolutional neural network (cnn) and support vector machine (svm) for image classification. arXiv preprint arXiv:1712.03541 2017."},{"issue":"114","key":"4645_CR16","first-page":"2","volume":"18","author":"G Cao","year":"2013","unstructured":"Cao G, Wang S, Wei B, Yin Y, Yang G. A hybrid cnn-rf method for electron microscopy images segmentation. J Biomim Biomater Tissue Eng. 2013;18(114):2.","journal-title":"J Biomim Biomater Tissue Eng"},{"key":"4645_CR17","doi-asserted-by":"publisher","first-page":"164507","DOI":"10.1109\/ACCESS.2019.2952946","volume":"7","author":"X Sun","year":"2019","unstructured":"Sun X, Liu L, Li C, Yin J, Zhao J, Si W. Classification for remote sensing data with improved cnn-svm method. IEEE Access. 2019;7:164507\u201316.","journal-title":"IEEE Access"},{"issue":"9","key":"4645_CR18","doi-asserted-by":"publisher","first-page":"854","DOI":"10.1080\/2150704X.2019.1629707","volume":"10","author":"H Feng","year":"2019","unstructured":"Feng H, Zou B, Ding Y. Satellite detection of aerosol-produced temperature change. Remote Sens Lett. 2019;10(9):854\u201363.","journal-title":"Remote Sens Lett"},{"key":"4645_CR19","doi-asserted-by":"publisher","first-page":"3411","DOI":"10.1007\/s11042-018-5986-5","volume":"78","author":"T Li","year":"2019","unstructured":"Li T, Leng J, Kong L, Guo S, Bai G, Wang K. Dcnr: deep cube cnn with random forest for hyperspectral image classification. Multimedia Tools Appl. 2019;78:3411\u201333.","journal-title":"Multimedia Tools Appl."},{"issue":"6","key":"4645_CR20","doi-asserted-by":"publisher","first-page":"3226","DOI":"10.1016\/j.jksuci.2020.12.010","volume":"34","author":"R Mostafiz","year":"2022","unstructured":"Mostafiz R, Uddin MS, Reza MM, Rahman MM. Covid-19 detection in chest x-ray through random forest classifier using a hybridization of deep cnn and dwt optimized features. J King Saud Univ Comput Inform Sci. 2022;34(6):3226\u201335.","journal-title":"J King Saud Univ Comput Inform Sci"},{"key":"4645_CR21","doi-asserted-by":"crossref","unstructured":"Kannojia, SP, Jaiswal G. Ensemble of hybrid cnn-elm model for image classification. In: 2018 5th international conference on signal processing and integrated networks (SPIN), 2018:538\u2013541, IEEE.","DOI":"10.1109\/SPIN.2018.8474196"},{"key":"4645_CR22","doi-asserted-by":"publisher","DOI":"10.3390\/cli13010016","author":"M Yarmohamadi","year":"2025","unstructured":"Yarmohamadi M, Alesheikh AA, Sharif M. Using hybrid deep learning models to predict dust storm pathways with enhanced accuracy. Climate. 2025. https:\/\/doi.org\/10.3390\/cli13010016.","journal-title":"Climate"},{"key":"4645_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jastp.2025.106448","volume":"268","author":"K Saha","year":"2025","unstructured":"Saha K, Bisht DS, Ashrit R. Prediction of lightning events over Bangladesh: a machine learning perspective. J Atmos Solar Terr Phys. 2025;268:106448. https:\/\/doi.org\/10.1016\/j.jastp.2025.106448.","journal-title":"J Atmos Solar Terr Phys"},{"key":"4645_CR24","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.procs.2024.12.015","volume":"252","author":"H Tarwani","year":"2025","unstructured":"Tarwani H, Patel S, Goel P. Deep learning approach for weather classification using pre-trained convolutional neural networks. Proc Comput Sci. 2025;252:136\u201345. https:\/\/doi.org\/10.1016\/j.procs.2024.12.015. (4th international conference on evolutionary computing and mobile sustainable networks).","journal-title":"Proc Comput Sci"},{"issue":"1","key":"4645_CR25","doi-asserted-by":"publisher","first-page":"44","DOI":"10.22581\/muet1982.2905","volume":"44","author":"A Nahar","year":"2025","unstructured":"Nahar A, Rudro RAM, Faisal BA, Sohan MFAA, Kumar L. Weather identification using models based on deep learning. Mehran Univ Res J Eng Technol. 2025;44(1):44\u201351. https:\/\/doi.org\/10.22581\/muet1982.2905.","journal-title":"Mehran Univ Res J Eng Technol"},{"key":"4645_CR26","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1016\/j.procs.2023.10.587","volume":"227","author":"K Purwandari","year":"2023","unstructured":"Purwandari K, Sigalingging JWC, Hidayat AA, Cenggoro TW, Pardamean B. Implementation of computer vision of Jakarta weather image categorization using resnet. Proc Comput Sci. 2023;227:813\u201322. https:\/\/doi.org\/10.1016\/j.procs.2023.10.587. (8th international conference on computer science and computational intelligence (ICCSCI 2023)).","journal-title":"Proc Comput Sci"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04645-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-025-04645-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04645-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T09:21:35Z","timestamp":1767000095000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-025-04645-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,29]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["4645"],"URL":"https:\/\/doi.org\/10.1007\/s42979-025-04645-3","relation":{},"ISSN":["2661-8907"],"issn-type":[{"value":"2661-8907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,29]]},"assertion":[{"value":"19 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}],"article-number":"58"}}