iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.crossref.org/works/10.1016/J.IMAVIS.2020.104036
{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T12:33:04Z","timestamp":1723033984288},"reference-count":43,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61403412"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Image and Vision Computing"],"published-print":{"date-parts":[[2020,11]]},"DOI":"10.1016\/j.imavis.2020.104036","type":"journal-article","created":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T06:44:33Z","timestamp":1601448273000},"page":"104036","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":25,"special_numbering":"C","title":["R4 Det: Refined single-stage detector with feature recursion and refinement for rotating object detection in aerial images"],"prefix":"10.1016","volume":"103","author":[{"given":"Peng","family":"Sun","sequence":"first","affiliation":[]},{"given":"Yongbin","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Zongtan","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Wanying","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Qiang","family":"Ren","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"7","key":"10.1016\/j.imavis.2020.104036_bb0005","doi-asserted-by":"crossref","first-page":"3965","DOI":"10.1109\/TGRS.2017.2685945","article-title":"Aid: a benchmark data set for performance evaluation of aerial scene classification","volume":"55","author":"Xia","year":"2017","journal-title":"IEEE Trans. Geoence Remote Sensing"},{"key":"10.1016\/j.imavis.2020.104036_bb0010","series-title":"Proceedings of the International Conference on Pattern Recognition Applications and Methods","first-page":"324","article-title":"A high resolution optical satellite image dataset for ship recognition and some new baselines","author":"Liu","year":"2017"},{"key":"10.1016\/j.imavis.2020.104036_bb0015","series-title":"Proceedings of 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"3974","article-title":"Dota: A large-scale dataset for object detection in aerial images","author":"Xia","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0020","doi-asserted-by":"crossref","first-page":"103910","DOI":"10.1016\/j.imavis.2020.103910","article-title":"Recent advances in small object detection based on deep learning: a review","volume":"97","author":"Kang","year":"2020","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.imavis.2020.104036_bb0025","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"779","article-title":"You only look once: Unified, real-time object detection","author":"Redmon","year":"2016"},{"issue":"2","key":"10.1016\/j.imavis.2020.104036_bb0030","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal loss for dense object detection","volume":"42","author":"Lin","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"10.1016\/j.imavis.2020.104036_bb0035","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster r-cnn: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.imavis.2020.104036_bb0040","article-title":"Cascade r-cnn: high quality object detection and instance segmentation","author":"Cai","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"10.1016\/j.imavis.2020.104036_bb0045","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s11263-019-01247-4","article-title":"Deep learning for generic object detection: a survey","volume":"128","author":"Liu","year":"2020","journal-title":"Int. J. Comput. Vis."},{"issue":"11","key":"10.1016\/j.imavis.2020.104036_bb0050","doi-asserted-by":"crossref","first-page":"3111","DOI":"10.1109\/TMM.2018.2818020","article-title":"Arbitrary-oriented scene text detection via rotation proposals","volume":"20","author":"Ma","year":"2018","journal-title":"IEEE Trans. Multimedia"},{"key":"10.1016\/j.imavis.2020.104036_bb0055","series-title":"Proceedings of 2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"8232","article-title":"Scrdet: Towards more robust detection for small, cluttered and rotated objects","author":"Yang","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0060","first-page":"1","article-title":"Gliding vertex on the horizontal bounding box for multi-oriented object detection","author":"Xu","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.imavis.2020.104036_bb0065","series-title":"Proceedings of 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"2849","article-title":"Learning roi transformer for detecting oriented objects in aerial images","author":"Ding","year":"2019"},{"key":"10.1016\/j.imavis.2020.104036_bb0070","series-title":"R3det: Refined single-stage detector with feature refinement for rotating object","author":"Yang","year":"2019"},{"key":"10.1016\/j.imavis.2020.104036_bb0075","series-title":"Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution","author":"Qiao","year":"2020"},{"key":"10.1016\/j.imavis.2020.104036_bb0080","series-title":"Recurrent neural network regularization","author":"Zaremba","year":"2014"},{"key":"10.1016\/j.imavis.2020.104036_bb0085","series-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"936","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017"},{"key":"10.1016\/j.imavis.2020.104036_bb0090","series-title":"Proceedings of the 30th International Conference on Neural Information Processing Systems","first-page":"379","article-title":"R-fcn: Object detection via region-based fully convolutional networks","author":"Dai","year":"2016"},{"issue":"2","key":"10.1016\/j.imavis.2020.104036_bb0095","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1109\/TPAMI.2018.2844175","article-title":"Mask r-cnn","volume":"42","author":"He","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.imavis.2020.104036_bb0100","series-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Overfeat: Integrated recognition, localization and detection using convolutional networks","author":"Sermanet","year":"2013"},{"key":"10.1016\/j.imavis.2020.104036_bb0105","series-title":"Proceedings of European Conference on Computer Vision","first-page":"21","article-title":"Ssd: Single shot multibox detector","author":"Liu","year":"2019"},{"key":"10.1016\/j.imavis.2020.104036_bb0110","series-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4203","article-title":"Path aggregation network for instance segmentation","author":"Liu","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0115","article-title":"Deep high-resolution representation learning for visual recognition","author":"Wang","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.imavis.2020.104036_bb0120","series-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"7036","article-title":"Nas-fpn: Learning scalable feature pyramid architecture for object detection","author":"Ghiasi","year":"2019"},{"key":"10.1016\/j.imavis.2020.104036_bb0125","series-title":"Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence","first-page":"11653","article-title":"Cbnet:A novel composite backbone network architecture for object detection","volume":"vol. 34","author":"Liu","year":"2020"},{"key":"10.1016\/j.imavis.2020.104036_bb0130","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.imavis.2018.09.008","article-title":"N., a coupled encoder-decoder network for joint face detection and landmark localization","volume":"87","author":"Lezi","year":"2019","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.imavis.2020.104036_bb0135","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.imavis.2020.104036_bb0140","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"3974","article-title":"Denseaspp for semantic segmentation in street scenes","author":"Yang","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0145","series-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4203","article-title":"Single-shot refinement neural network for object detection","author":"Zhang","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0150","series-title":"Proceedings of AAAI Conference on Artificial Intelligence","first-page":"6773","article-title":"Pixellink: Detecting scene text via instance segmentation","author":"Deng","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0155","series-title":"Mmdetection: Open mmlab detection toolbox and benchmark","author":"Chen","year":"2019"},{"issue":"6","key":"10.1016\/j.imavis.2020.104036_bb0160","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"Imagenet classification with deep convolutional neural networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun. ACM"},{"issue":"7","key":"10.1016\/j.imavis.2020.104036_bb0165","first-page":"11908","article-title":"Ffa-net: feature fusion attention network for single image dehazing","volume":"34","author":"Qin","year":"2020","journal-title":"Proce. Thirty-Fourth AAAI Conf. Artificial Intel."},{"key":"10.1016\/j.imavis.2020.104036_bb0170","first-page":"1","article-title":"Adaptive period embedding for representing oriented objects in aerial images","author":"Zhu","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.imavis.2020.104036_bb0175","series-title":"Ienet: interacting embranchment one stage anchor free detector for orientation aerial object detection","author":"Lin","year":"2019"},{"key":"10.1016\/j.imavis.2020.104036_bb0180","series-title":"Proceedings of the International Conference on Pattern Recognition (ICPR)","first-page":"3610","article-title":"R2cnn: Rotational region cnn for orientation robust scene text detection","author":"Jiang","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0185","series-title":"Learning modulated loss for rotated object detection","author":"Qian","year":"2019"},{"issue":"11","key":"10.1016\/j.imavis.2020.104036_bb0190","doi-asserted-by":"crossref","first-page":"1745","DOI":"10.1109\/LGRS.2018.2856921","article-title":"Toward arbitrary-oriented ship detection with rotated region proposal and discrimination networks","volume":"15","author":"Zenghui","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.imavis.2020.104036_bb0195","series-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","first-page":"5909","article-title":"Rotation-sensitive regression for oriented scene text detection","author":"Liao","year":"2018"},{"key":"10.1016\/j.imavis.2020.104036_bb0200","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"49","article-title":"Fooling automated surveillance cameras: Adversarial patches to attack person detection","author":"Thys","year":"2019"},{"issue":"2","key":"10.1016\/j.imavis.2020.104036_bb0205","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s11633-019-1211-x","article-title":"Adversarial attacks and defenses in images, graphs and text: a review","volume":"17","author":"Xu","year":"2020","journal-title":"Int. J. Autom. Comput."},{"key":"10.1016\/j.imavis.2020.104036_bb0210","series-title":"Adversarial patch camouflage against aerial detection","author":"Ajaya","year":"2020"},{"key":"10.1016\/j.imavis.2020.104036_bb0215","doi-asserted-by":"crossref","first-page":"103926","DOI":"10.1016\/j.imavis.2020.103926","article-title":"Class-aware domain adaptation for improving adversarial robustness","volume":"99","author":"Xianxu","year":"2020","journal-title":"Image Vis. Comput."}],"container-title":["Image and Vision Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0262885620301682?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0262885620301682?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T22:54:34Z","timestamp":1668639274000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0262885620301682"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11]]},"references-count":43,"alternative-id":["S0262885620301682"],"URL":"https:\/\/doi.org\/10.1016\/j.imavis.2020.104036","relation":{},"ISSN":["0262-8856"],"issn-type":[{"value":"0262-8856","type":"print"}],"subject":[],"published":{"date-parts":[[2020,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"R4 Det: Refined single-stage detector with feature recursion and refinement for rotating object detection in aerial images","name":"articletitle","label":"Article Title"},{"value":"Image and Vision Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.imavis.2020.104036","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"104036"}}