{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T02:38:05Z","timestamp":1725763085859},"reference-count":9,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T00:00:00Z","timestamp":1658016000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T00:00:00Z","timestamp":1658016000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,17]]},"DOI":"10.1109\/igarss46834.2022.9883949","type":"proceedings-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T20:12:24Z","timestamp":1664395944000},"page":"191-194","source":"Crossref","is-referenced-by-count":2,"title":["Earth Observation Data Classification with Quantum-Classical Convolutional Neural Network"],"prefix":"10.1109","author":[{"given":"Fan","family":"Fan","sequence":"first","affiliation":[{"name":"Technical University of Munich (TUM),Data Science in Earth Observation,Munich,Germany"}]},{"given":"Yilei","family":"Shi","sequence":"additional","affiliation":[{"name":"Technical University of Munich (TUM),Remote Sensing Technology,Munich,Germany"}]},{"given":"Xiao Xiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Technical University of Munich (TUM),Data Science in Earth Observation,Munich,Germany"}]}],"member":"263","reference":[{"key":"ref4","article-title":"On circuit-based hybrid quantum neural networks for re-mote sensing imagery classification","author":"sebastianelli","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS39084.2020.9323065"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11128-010-0177-y"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1088\/2058-9565\/ab9f93"},{"key":"ref8","article-title":"Overhead mnist: A benchmark satellite dataset","author":"noever","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref7","article-title":"Quantum pixel rep-resentations and compression for n-dimensional images","author":"amankwah","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2021.3095377"},{"key":"ref9","article-title":"Tensorflow quantum: A soft-ware framework for quantum machine learning","author":"broughton","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref1","first-page":"1973","article-title":"Approaching re-mote sensing image classification with ensembles of sup-port vector machines on the d-wave quantum annealer","author":"cavallaro","year":"2020","journal-title":"2010 IEEE International Geoscience and Remote Sensing Symposium IGARSS"}],"event":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","start":{"date-parts":[[2022,7,17]]},"location":"Kuala Lumpur, Malaysia","end":{"date-parts":[[2022,7,22]]}},"container-title":["IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9883023\/9883024\/09883949.pdf?arnumber=9883949","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T20:52:05Z","timestamp":1665780725000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9883949\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,17]]},"references-count":9,"URL":"https:\/\/doi.org\/10.1109\/igarss46834.2022.9883949","relation":{},"subject":[],"published":{"date-parts":[[2022,7,17]]}}}