{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T04:23:43Z","timestamp":1769574223659,"version":"3.49.0"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Missouri Department of Conservation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2020,10]]},"DOI":"10.1109\/tgrs.2020.2980023","type":"journal-article","created":{"date-parts":[[2020,3,25]],"date-time":"2020-03-25T20:43:01Z","timestamp":1585168981000},"page":"7154-7165","source":"Crossref","is-referenced-by-count":29,"title":["Adaptive Saliency Biased Loss for Object Detection in Aerial Images"],"prefix":"10.1109","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4715-5926","authenticated-orcid":false,"given":"Peng","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7771-4034","authenticated-orcid":false,"given":"Yi","family":"Shang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.237"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.596"},{"key":"ref33","article-title":"Machine learning from imbalanced data sets 101","volume":"68","author":"provost","year":"2000","journal-title":"Proc AAAI Workshop Learning Imbalanced Data Sets"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2374218"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2867198"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2601622"},{"key":"ref37","first-page":"391","article-title":"Edge boxes: Locating object proposals from edges","volume":"8693","author":"zitnick","year":"2014","journal-title":"Vision Computer"},{"key":"ref36","article-title":"DSSD: Deconvolutional single shot detector","author":"fu","year":"2017","journal-title":"arXiv 1701 06659"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.205"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.89"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2875597"},{"key":"ref11","first-page":"21","article-title":"SSD: Single shot multibox detector","volume":"9905","author":"liu","year":"2016","journal-title":"Vision Computer"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2017.00016"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/s17020336"},{"key":"ref14","article-title":"Deep learning based multi-category object detection in aerial images","author":"sommer","year":"2017","journal-title":"Proceedings of Automatic Target Recognition"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"132","DOI":"10.3390\/rs10010132","article-title":"Automatic ship detection in remote sensing images from Google Earth of complex scenes based on multiscale rotation dense feature pyramid networks","volume":"10","author":"yang","year":"2018","journal-title":"Remote Sens"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref17","first-page":"740","article-title":"Microsoft COCO: Common objects in context","volume":"8693","author":"lin","year":"2014","journal-title":"Vision Computer"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858826"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/SMARTCOMP.2016.7501676"},{"key":"ref28","article-title":"Salience biased loss for object detection in aerial images","author":"sun","year":"2018","journal-title":"arXiv 1810 08103"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2778300"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2016.03.014"},{"key":"ref5","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"ren","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref8","article-title":"YOLO9000: Better, faster, stronger","author":"redmon","year":"2016","journal-title":"arXiv 1612 08242"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref2","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref9","first-page":"379","article-title":"R-FCN: Object detection via region-based fully convolutional networks","author":"dai","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref1","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CCNC.2017.7983278"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3390\/s18082702"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00418"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2014.10.002"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2567393"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref23","article-title":"Towards multi-class object detection in unconstrained remote sensing imagery","author":"majid azimi","year":"2018","journal-title":"arXiv 1807 02700"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01240-3_4"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-016-0907-4"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/9205700\/09047153.pdf?arnumber=9047153","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:11:24Z","timestamp":1651068684000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9047153\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10]]},"references-count":42,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tgrs.2020.2980023","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10]]}}}