[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-31225":3,"doc-seo-31225":27},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"file_id":15,"file_url":16,"file_type":17,"file_size":18,"view_count":4,"is_deleted":4,"is_public":19,"is_downloadable":19,"audit_status":19,"page_count":20,"language":21,"language_code":22,"table_of_contents":23,"faqs":24,"seo_title":13,"seo_description":14,"update_tm":25,"read_time":26},31225,1649267921044,"Ava Thompson","https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1779183583414876462",8,"Research & Report","On Circuit-Based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification","The article investigates circuit-based hybrid quantum convolutional neural networks as image classifiers for remote sensing. A quantum layer is integrated into a standard convolutional neural network to form the proposed hybrid QCNN architecture. The approach is evaluated on land-use and land-cover classification using the EuroSAT dataset as the benchmark. Multiclass results show higher performance than classical baselines, and circuit analysis indicates that quantum-entanglement–exploiting circuits yield the best scores. The study supports quantum computing potential for Earth observation and motivates future work with both theoretical and experimental foundations.","cbCaiqRTkf3dmf4x","https://ap.wps.com/l/cbCaiqRTkf3dmf4x","pdf",4821977,1,16,"English","en","# Introduction\n## Earth observation and big data context\n## Quantum computing background and limitations\n## Quantum algorithms and hybrid computation\n## Qubits and basic quantum information","[{\"question\":\"What does the proposed hybrid quantum convolutional neural network add to a classical CNN?\",\"answer\":\"It enriches the classical convolutional neural network architecture by introducing a quantum layer within a standard neural network pipeline.\"},{\"question\":\"Which remote sensing task and dataset are used to evaluate the method?\",\"answer\":\"The method is applied to land-use and land-cover classification and tested using the EuroSAT dataset as the reference benchmark.\"},{\"question\":\"Why do circuits using quantum entanglement perform better in the study?\",\"answer\":\"The investigation of various quantum circuits shows that those exploiting quantum entanglement achieve the best classification scores.\"}]",1779224457,40,{"code":4,"msg":28,"data":29},"ok",{"site_id":30,"language":22,"slug":31,"title":13,"keywords":32,"description":14,"schema_data":33,"social_meta":84,"head_meta":86,"extra_data":88,"updated_unix":25},105,"on-circuit-based-hybrid-quantum-neural-networks-for-remote-sensing-imagery-classification","",{"@graph":34,"@context":83},[35,52,66],{"@type":36,"itemListElement":37},"BreadcrumbList",[38,42,46,49],{"item":39,"name":40,"@type":41,"position":19},"https://docshare.wps.com","Home","ListItem",{"item":43,"name":44,"@type":41,"position":45},"https://docshare.wps.com/document/","Document",2,{"item":47,"name":12,"@type":41,"position":48},"https://docshare.wps.com/document/research-report/",3,{"item":50,"name":13,"@type":41,"position":51},"https://docshare.wps.com/document/on-circuit-based-hybrid-quantum-neural-networks-for-remote-sensing-imagery-classification/31225/",4,{"url":50,"name":13,"@type":53,"author":54,"headline":13,"publisher":56,"fileFormat":59,"description":14,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":39,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-05-19",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69,75,79],{"name":70,"@type":71,"acceptedAnswer":72},"What does the proposed hybrid quantum convolutional neural network add to a classical CNN?","Question",{"text":73,"@type":74},"It enriches the classical convolutional neural network architecture by introducing a quantum layer within a standard neural network pipeline.","Answer",{"name":76,"@type":71,"acceptedAnswer":77},"Which remote sensing task and dataset are used to evaluate the method?",{"text":78,"@type":74},"The method is applied to land-use and land-cover classification and tested using the EuroSAT dataset as the reference benchmark.",{"name":80,"@type":71,"acceptedAnswer":81},"Why do circuits using quantum entanglement perform better in the study?",{"text":82,"@type":74},"The investigation of various quantum circuits shows that those exploiting quantum entanglement achieve the best classification scores.","https://schema.org",{"og:url":50,"og:type":85,"og:title":13,"og:site_name":57,"og:description":14},"article",{"robots":87,"canonical":50},"index,follow",{"doc_id":7,"site_id":30}]