{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:05:55Z","timestamp":1730264755511,"version":"3.28.0"},"reference-count":10,"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\/igarss46834.2022.9883543","type":"proceedings-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T20:12:24Z","timestamp":1664395944000},"page":"819-822","source":"Crossref","is-referenced-by-count":0,"title":["Levels of Supervision for Object Classification in Overhead Imagery"],"prefix":"10.1109","author":[{"given":"Kristina","family":"Lawson","sequence":"first","affiliation":[{"name":"Virginia Polytechnic Institute and State University,Bradley Department of Electrical and Computer Engineering,Virginia,USA"}]},{"given":"Nektaria","family":"Tryfona","sequence":"additional","affiliation":[{"name":"Virginia Polytechnic Institute and State University,Bradley Department of Electrical and Computer Engineering,Virginia,USA"}]}],"member":"263","reference":[{"journal-title":"Semi-supervised image classification on imagenet - 1% labeled data","year":"0","key":"ref4"},{"journal-title":"Dota A large-scale dataset for object detection in aerial images","year":"2018","author":"xia","key":"ref3"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref6","article-title":"Big self-supervised models are strong semi-supervised learners","volume":"abs 2006 10029","author":"chen","year":"2020","journal-title":"CoRR"},{"journal-title":"Semi-supervised image classification on imagenet - 10% labeled data","year":"0","key":"ref5"},{"key":"ref8","first-page":"1","article-title":"Contrastive self-supervised learning with smoothed representation for remote sensing","author":"jung","year":"2021","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"ref7","article-title":"A simple framework for contrastive learning of visual representations","volume":"abs 2002 5709","author":"chen","year":"2020","journal-title":"CoRR"},{"journal-title":"Fair1m A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery","year":"2021","author":"sun","key":"ref2"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00129"},{"journal-title":"xview Objects in context in overhead imagery","year":"2018","author":"lam","key":"ref1"}],"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\/09883543.pdf?arnumber=9883543","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T20:52:50Z","timestamp":1665780770000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9883543\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,17]]},"references-count":10,"URL":"https:\/\/doi.org\/10.1109\/igarss46834.2022.9883543","relation":{},"subject":[],"published":{"date-parts":[[2022,7,17]]}}}