{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T15:20:36Z","timestamp":1773847236772,"version":"3.50.1"},"reference-count":68,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100032796","name":"JSS Academy of Technical Education, Noida","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100032796","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.engappai.2025.113195","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T14:38:59Z","timestamp":1763649539000},"page":"113195","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"PA","title":["Quantum convolutional neural network-based hybrid network for remote sensing image classification"],"prefix":"10.1016","volume":"164","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3854-5500","authenticated-orcid":false,"given":"H.N.","family":"Mahendra","sequence":"first","affiliation":[]},{"given":"V.","family":"Pushpalatha","sequence":"additional","affiliation":[]},{"given":"S.","family":"Mallikarjunaswamy","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8097-2314","authenticated-orcid":false,"given":"S.","family":"Rama Subramoniam","sequence":"additional","affiliation":[]},{"given":"J.","family":"Praveen","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2025.113195_bib1","doi-asserted-by":"crossref","first-page":"13027","DOI":"10.1007\/s00500-021-06460-3","article-title":"Quantum neural network-based multilabel image classification in high-resolution unmanned aerial vehicle imagery","volume":"27","author":"Abdel-Khalek","year":"2023","journal-title":"Soft Comput."},{"key":"10.1016\/j.engappai.2025.113195_bib2","doi-asserted-by":"crossref","first-page":"2612","DOI":"10.1016\/j.procs.2023.01.235","article-title":"Quantum machine learning: scope for real-world problems","volume":"218","author":"Abhishek","year":"2023","journal-title":"Procedia Comput. Sci."},{"key":"10.1016\/j.engappai.2025.113195_bib3","article-title":"Classification with quantum machine learning: a survey","author":"Abohashima","year":"2020","journal-title":"arXiv:2006.12270"},{"key":"10.1016\/j.engappai.2025.113195_bib4","first-page":"328","article-title":"A Swin Transformer-based method for classification of land use and land cover images","volume":"16","author":"Ali","year":"2024","journal-title":"Int. J. Adv. Soft Comput. Its Appl."},{"key":"10.1016\/j.engappai.2025.113195_bib5","article-title":"Quantum image processing","author":"Anand","year":"2022","journal-title":"arXiv:2203.01831"},{"issue":"2","key":"10.1016\/j.engappai.2025.113195_bib6","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/s41651-022-00130-0","article-title":"Comparing pan-sharpened Landsat-9 and Sentinel-2 for land-use classification using machine learning classifiers","volume":"6","author":"Bouslihim","year":"2022","journal-title":"Journal of Geovisualization and Spatial Analysis"},{"issue":"2","key":"10.1016\/j.engappai.2025.113195_bib7","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0172505","article-title":"Deploying a quantum annealing processor to detect tree cover in aerial imagery of California","volume":"12","author":"Boyda","year":"2017","journal-title":"PLoS One"},{"key":"10.1016\/j.engappai.2025.113195_bib8","series-title":"IEEE Int. Geosci. Remote Sens. Symp.","first-page":"1973","article-title":"Approaching remote sensing image classification with ensembles of support vector machines on the D-wave quantum annealer","author":"Cavallaro","year":"2020"},{"key":"10.1016\/j.engappai.2025.113195_bib9","doi-asserted-by":"crossref","first-page":"3735","DOI":"10.1109\/JSTARS.2020.3005403","article-title":"Remote sensing image scene classification meets deep learning: challenges, methods, benchmarks, and opportunities","volume":"13","author":"Cheng","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib10","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1080\/17538947.2023.2177359","article-title":"A landslide extraction method of channel attention mechanism U-Net network based on Sentinel-2A remote sensing images","volume":"16","author":"Chen","year":"2023","journal-title":"International Journal of Digital Earth"},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib11","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevResearch.4.013231","article-title":"Quantum convolutional neural networks for high energy physics data analysis","volume":"4","author":"Chen","year":"2022","journal-title":"Phys. Rev. Res."},{"key":"10.1016\/j.engappai.2025.113195_bib12","series-title":"Proc. 13th Int. Congr. Image Signal Process., Biomed. Eng. Informat","first-page":"243","article-title":"Quantum convolutional neural network on scale chaology","author":"Chen","year":"2020"},{"issue":"12","key":"10.1016\/j.engappai.2025.113195_bib13","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1038\/s41567-019-0648-8","article-title":"Quantum convolutional neural networks","volume":"15","author":"Cong","year":"2019","journal-title":"Nat. Phys."},{"issue":"9","key":"10.1016\/j.engappai.2025.113195_bib14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11128-018-2004-9","article-title":"Image classification based on quantum K-nearest-neighbor algorithm","volume":"17","author":"Dang","year":"2018","journal-title":"Quant. Inf. Process."},{"key":"10.1016\/j.engappai.2025.113195_bib15","series-title":"IEEE Int. Geosci. Remote Sens. Symp.","first-page":"2608","article-title":"Quantum support vector machine algorithms for remote sensing data classification","author":"Delilbasic","year":"2021"},{"key":"10.1016\/j.engappai.2025.113195_bib16","doi-asserted-by":"crossref","first-page":"3070","DOI":"10.1109\/JSTARS.2021.3062635","article-title":"Remote sensing image classification using deep\u2013shallow learning","volume":"14","author":"Dou","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"issue":"18","key":"10.1016\/j.engappai.2025.113195_bib17","doi-asserted-by":"crossref","first-page":"2956","DOI":"10.3390\/rs12182956","article-title":"Hyperspectral image classification using feature relations map learning","volume":"12","author":"Dou","year":"2020","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib18","doi-asserted-by":"crossref","first-page":"12477","DOI":"10.1109\/JSTARS.2024.3411670","article-title":"Land cover classification from Sentinel-2 images with quantum-classical convolutional neural networks","volume":"17","author":"Fan","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib19","article-title":"Hybrid quantum-classical convolutional neural network model for image classification","author":"Fan","year":"2023","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"key":"10.1016\/j.engappai.2025.113195_bib20","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1109\/TNNLS.2013.2274436","article-title":"Quantum neural network-based EEG filtering for a brain-computer interface","volume":"25","author":"Gandhi","year":"2014","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"key":"10.1016\/j.engappai.2025.113195_bib21","series-title":"IEEE Int. Geosci. Remote Sens. Symp.","first-page":"3513","article-title":"Multi-spectral image classification with quantum neural network","author":"Gawron","year":"2020"},{"issue":"7747","key":"10.1016\/j.engappai.2025.113195_bib22","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1038\/s41586-019-0980-2","article-title":"Supervised learning with quantum-enhanced feature spaces","volume":"567","author":"Havlicek","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.engappai.2025.113195_bib23","doi-asserted-by":"crossref","first-page":"6732","DOI":"10.1109\/JSTARS.2022.3198728","article-title":"Time-series analysis and prediction of surface deformation in the Jinchuan mining area, Gansu Province, by using InSAR and CNN\u2013PhLSTM network","volume":"15","author":"He","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib24","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/s42484-020-00012-y","article-title":"Quanvolutional neural networks: powering image recognition with quantum circuits","volume":"2","author":"Henderson","year":"2020","journal-title":"Quantum Machine Intelligence"},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib25","doi-asserted-by":"crossref","first-page":"4144","DOI":"10.1038\/s41467-022-31679-5","article-title":"Realizing quantum convolutional neural networks on a superconducting quantum processor to recognize quantum phases","volume":"13","author":"Herrmann","year":"2022","journal-title":"Nat. Commun."},{"key":"10.1016\/j.engappai.2025.113195_bib26","series-title":"Proc. SPIE 13196, Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX, 131960O","article-title":"Remote sensing classification using quantum image processing","author":"Hrithik","year":"2024"},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib27","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s42484-021-00061-x","article-title":"Quantum convolutional neural network for classical data classification","volume":"4","author":"Hur","year":"2022","journal-title":"Quantum Machine Intelligence"},{"key":"10.1016\/j.engappai.2025.113195_bib28","article-title":"Learning to learn variational quantum algorithm","author":"Huang","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst., early access, Feb. 28"},{"issue":"3","key":"10.1016\/j.engappai.2025.113195_bib29","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s11128-022-03442-8","article-title":"RGB image classification with quantum convolutional ansatz","volume":"21","author":"Jing","year":"2022","journal-title":"Quant. Inf. Process."},{"key":"10.1016\/j.engappai.2025.113195_bib30","article-title":"Quantum algorithms for deep convolutional neural networks","author":"Kerenidis","year":"2019","journal-title":"arXiv:1911.01117"},{"key":"10.1016\/j.engappai.2025.113195_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.126843","article-title":"Advances in quantum machine learning and deep learning for image classification: a survey","volume":"560","author":"Kharsa","year":"2023","journal-title":"Neurocomputing"},{"key":"10.1016\/j.engappai.2025.113195_bib32","article-title":"Transformer-based land use and land cover classification with explainability using satellite imagery","volume":"14","author":"Khan","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.engappai.2025.113195_bib33","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.126643","article-title":"Classical-to-quantum convolutional neural network transfer learning","volume":"555","author":"Kim","year":"2023","journal-title":"Neurocomputing"},{"issue":"11","key":"10.1016\/j.engappai.2025.113195_bib34","doi-asserted-by":"crossref","first-page":"6331","DOI":"10.1109\/TNNLS.2021.3077188","article-title":"Qutrit-inspired fully self-supervised shallow quantum learning network for brain tumor segmentation","volume":"33","author":"Konar","year":"2022","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"issue":"4","key":"10.1016\/j.engappai.2025.113195_bib36","doi-asserted-by":"crossref","DOI":"10.1088\/2058-9565\/ab9f93","article-title":"A quantum deep convolutional neural network for image recognition","volume":"5","author":"Li","year":"2020","journal-title":"Quantum Sci. Technol."},{"issue":"12","key":"10.1016\/j.engappai.2025.113195_bib37","doi-asserted-by":"crossref","first-page":"23","DOI":"10.55708\/js0212004","article-title":"Quantum machine learning on remote sensing data classification","volume":"2","author":"Liu","year":"2023","journal-title":"Journal of Engineering Research and Sciences"},{"key":"10.1016\/j.engappai.2025.113195_bib38","series-title":"IEEE Int. Geosci. Remote Sens. Symp.","first-page":"7807","article-title":"Quantum adversarial learning for hyperspectral remote sensing","author":"Lin","year":"2024"},{"key":"10.1016\/j.engappai.2025.113195_bib39","series-title":"Proc. 40th Chin. Control Conf. (CCC)","first-page":"6329","article-title":"A quantum convolutional neural network for image classification","author":"Lu","year":"2021"},{"key":"10.1016\/j.engappai.2025.113195_bib40","doi-asserted-by":"crossref","DOI":"10.1016\/j.asr.2024.07.066","article-title":"LULC change detection analysis of Chamarajanagar District, Karnataka State, India using CNN-based deep learning method","volume":"74","author":"Mahendra","year":"2024","journal-title":"Adv. Space Res."},{"key":"10.1016\/j.engappai.2025.113195_bib41","series-title":"IEEE Int. Conf. Quantum Comput. Eng. (QCE)","first-page":"56","article-title":"Quantum-classical convolutional neural networks in radiological image classification","author":"Matic","year":"2022"},{"key":"10.1016\/j.engappai.2025.113195_bib42","series-title":"2024 IEEE Aerospace Conference, Big Sky","first-page":"1","article-title":"Quantum image fusion methods for remote sensing","author":"Miller","year":"2024"},{"key":"10.1016\/j.engappai.2025.113195_bib43","series-title":"Quantum Computation and Quantum Information","author":"Nielsen","year":"2010"},{"issue":"7","key":"10.1016\/j.engappai.2025.113195_bib44","first-page":"2522","article-title":"Benchmarking neural networks for quantum computations","volume":"31","author":"Nguyen","year":"2020","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"key":"10.1016\/j.engappai.2025.113195_bib45","article-title":"Quantum image classification using principal component analysis","author":"Ostaszewski","year":"2015","journal-title":"arXiv:1504.00580"},{"key":"10.1016\/j.engappai.2025.113195_bib46","doi-asserted-by":"crossref","DOI":"10.1109\/TGRS.2021.3110056","article-title":"Natural embedding of the Stokes parameters of polarimetric synthetic aperture radar images in a gate-based quantum computer","volume":"60","author":"Otgonbaatar","year":"2022","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib47","doi-asserted-by":"crossref","first-page":"7057","DOI":"10.1109\/JSTARS.2021.3095377","article-title":"A quantum annealer for subset feature selection and the classification of hyperspectral images","volume":"14","author":"Otgonbaatar","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib48","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.116112","article-title":"Hybrid classical\u2013quantum convolutional neural network for stenosis detection in X-ray coronary angiography","volume":"189","author":"Ovalle-Magallanes","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2025.113195_bib49","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.isprsjprs.2020.05.022","article-title":"Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters","volume":"166","author":"Pan","year":"2020","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib50","article-title":"EfficientNet B0 model for enhanced land use and land cover classification from satellite imagery","author":"Patil","year":"2025","journal-title":"SSRN"},{"key":"10.1016\/j.engappai.2025.113195_bib52","doi-asserted-by":"crossref","DOI":"10.1016\/j.acags.2025.100227","article-title":"Land use and land cover classification for change detection studies using convolutional neural network","volume":"25","author":"Pushpalatha","year":"2025","journal-title":"Applied Computing and Geosciences"},{"issue":"13","key":"10.1016\/j.engappai.2025.113195_bib53","doi-asserted-by":"crossref","DOI":"10.1103\/PhysRevLett.113.130503","article-title":"Quantum support vector machine for big data classification","volume":"113","author":"Rebentrost","year":"2014","journal-title":"Phys. Rev. Lett."},{"issue":"5","key":"10.1016\/j.engappai.2025.113195_bib54","doi-asserted-by":"crossref","first-page":"2753","DOI":"10.3390\/s23052753","article-title":"Accurate image multi-class classification neural network model with quantum entanglement approach","volume":"23","author":"Riaz","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.engappai.2025.113195_bib55","article-title":"Demonstration of quantum advantage in machine learning","volume":"3","author":"Rist\u00e8","year":"2015","journal-title":"npj Quantum Information"},{"issue":"11","key":"10.1016\/j.engappai.2025.113195_bib56","doi-asserted-by":"crossref","first-page":"3496","DOI":"10.1007\/s10773-017-3514-4","article-title":"Quantum algorithm for K-nearest neighbors classification based on the metric of Hamming distance","volume":"56","author":"Ruan","year":"2017","journal-title":"Int. J. Theor. Phys."},{"key":"10.1016\/j.engappai.2025.113195_bib57","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1109\/JSTARS.2021.3134785","article-title":"On circuit-based hybrid quantum neural networks for remote sensing imagery classification","volume":"15","author":"Sebastianelli","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens."},{"issue":"22","key":"10.1016\/j.engappai.2025.113195_bib58","doi-asserted-by":"crossref","first-page":"5774","DOI":"10.3390\/rs14225774","article-title":"Quantum based pseudo-labelling for hyperspectral imagery: a simple and efficient semi-supervised learning method for machine learning classifiers","volume":"14","author":"Shaik","year":"2022","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib59","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.isprsjprs.2019.11.004","article-title":"Building segmentation through a gated graph convolutional neural network with deep structured feature embedding","volume":"159","author":"Shi","year":"2020","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib60","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1109\/LGRS.2018.2878486","article-title":"Building footprint generation using improved generative adversarial networks","volume":"16","author":"Shi","year":"2018","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"10.1016\/j.engappai.2025.113195_bib61","doi-asserted-by":"crossref","first-page":"214520","DOI":"10.1109\/ACCESS.2020.3039996","article-title":"A new trend of quantum image representations","volume":"8","author":"Su","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib62","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s43673-021-00030-3","article-title":"A quantum convolutional neural network on NISQ devices","volume":"32","author":"Wei","year":"2022","journal-title":"AAPPS Bull."},{"issue":"1","key":"10.1016\/j.engappai.2025.113195_bib63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s42484-020-00022-w","article-title":"Optimizing quantum heuristics with meta-learning","volume":"3","author":"Wilson","year":"2021","journal-title":"Quantum Machine Intelligence"},{"key":"10.1016\/j.engappai.2025.113195_bib64","first-page":"1","article-title":"A convLSTM neural network model for spatiotemporal prediction of mining area surface deformation based on SBAS-InSAR monitoring data","volume":"61","author":"Yao","year":"2023","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib65","series-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS)","first-page":"5680","article-title":"Advantages and bottlenecks of quantum machine learning for remote sensing","author":"Zaidenberg","year":"2021"},{"issue":"3","key":"10.1016\/j.engappai.2025.113195_bib66","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3390\/e24030394","article-title":"A multiclassification hybrid quantum neural network using an all-qubit multiobservable measurement strategy","volume":"24","author":"Zeng","year":"2022","journal-title":"Entropy"},{"key":"10.1016\/j.engappai.2025.113195_bib67","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MGRS.2017.2762307","article-title":"Deep learning in remote sensing: a comprehensive review and list of resources","volume":"5","author":"Zhu","year":"2017","journal-title":"IEEE Geoscience and Remote Sensing Magazine"},{"key":"10.1016\/j.engappai.2025.113195_bib68","article-title":"Design of a quantum convolutional neural network on quantum circuits","author":"Zheng","year":"2022","journal-title":"J. Franklin Inst."},{"issue":"19","key":"10.1016\/j.engappai.2025.113195_bib69","doi-asserted-by":"crossref","first-page":"4883","DOI":"10.3390\/rs14194883","article-title":"Deep learning classification by ResNet-18 based on the real spectral dataset from multispectral remote sensing images","volume":"14","author":"Zhao","year":"2022","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2025.113195_bib70","volume":"24","author":"Zollner","year":"2024"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197625032269?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197625032269?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T09:56:32Z","timestamp":1773827792000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197625032269"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":68,"alternative-id":["S0952197625032269"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2025.113195","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Quantum convolutional neural network-based hybrid network for remote sensing image classification","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2025.113195","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"113195"}}