Computer Science ›› 2024, Vol. 51 ›› Issue (3): 165-173.doi: 10.11896/jsjkx.230200030
• Computer Graphics & Multimedia • Previous Articles Next Articles
ZHANG Yang, XIA Ying
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[1]SUN X,WANG P,YAN Z,et al.FAIR1M:A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery[J].ISPRS Journal of Photogrammetry and Remote Sensing,2022,184:116-130. [2]GIRSHICK R,DONAHUE J,DARRELL T,et al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2014:580-587. [3]REN S Q,HE K,GIRSHICK R,et al.Faster R-CNN:Towards Real-Time Object Detection with Region Proposal Networks[C]//Proceedings of the 28th International Conference on Neural Information Processing System.Montréal:MIT Press,2015:91-99. [4]DAI J,LI Y,HE K,et al.R-FCN:Object Detection via Region-based Fully Convolutional Networks[C]// Advances in Neural Information Processing Systems.Curran Associates Inc.,2016:379-387. [5]HE K,GKIOXARI G,DOLLÁR P,et al.Mask R-CNN[C]//Proceedings of the IEEE International Conference on Computer Vision.2017:2961-2969. [6]REDMON J,DIVVALA S,GIRSHICK R,et al.You only look once:Unified,real-time object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:779-788. [7]LIU W,ANGUELOV D,ERHAN D,et al.Ssd:Single shotmultibox detector[C]//EuropeanConference on Computer Vision.Cham:Springer,2016:21-37. [8]LIN T Y,GOYAL P,GIRSHICK R,et al.Focal loss for dense object detection[C]//Proceedings of the IEEE International Conference on Computer Vision.2017:2980-2988. [9]ZHANG L,ZHANG Y S,YU Y,et al.Survey on object detection in tilting box for remote sensing images[J].National Remote Sensing Bulletin,2022,26(9):1723-1743. [10]ZHU W T,LAN X C,LUO H L,et al.Remote Sensing Aircraft Target Detection Based on Improved Faster R-CNN[J].Computer Science,2022,49(S1):378-383. [11]SHA M M,LI Y,LI A.Multiscale aircraft detection in optical remote sensing imagery based on advanced Faster R-CNN[J].National Remote Sensing Bulletin,2022,26(8):1624-1635. [12]DENG R Z,CHEN Q H,CHEN Q,et al.A deformable feature pyramid network for ship detection from remote sensing images[J].Acta Geodaetica et CartographicaSinica,2020,49(6):787-797. [13]YU Y,AI H,HE X J,et al.Attention-based feature pyramid networks for ship detection of optical remote sensing image[J].National Remote Sensing Bulletin,2020,24(2):107-115. [14]ZHU M C,FENG T,ZHANG Y.Remote sensing image multi-target detection method based on FD-SSD[J].Computer Applications and Software,2019,36(1):238-244. [15]LIN T Y,DOLLÁR P,GIRSHICK R,et al.Feature pyramidnetworks for object detection[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2017:2117-2125. [16]JIANG S J,LUO B,HE P,et al.Vehicle Speed Detection by Multi-source Images from UAV[J].Acta Geodaetica et CartographicaSinica,2018,47(9):1228-1237. [17]YANG X,YAN J,FENG Z,et al.R3det:Refined single-stage detector with feature refinement for rotating object[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2021:3163-3171. [18]YANG X,YAN J.Arbitrary-oriented object detection with circular smooth label[C]//European Conference on Computer Vision.Cham:Springer,2020:677-694. [19]DING J,XUE N,LONG Y,et al.Learning roi transformer for oriented object detection in aerial images[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2019:2849-2858. [20]WANG J,CHEN Y,GAO M,et al.Improved YOLOv5 network for real-time multi-scale traffic sign detection[J].arXiv:2112.08782,2021. [21]ZHU X,LYU S,WANG X,et al.TPH-YOLOv5:ImprovedYOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.2021:2778-2788. [22]GLENN J,ALEX S,JIRKA B:YOLOv5[EB/OL].[2021-04-12].https://github.com/ultralytics/yolov5. [23]WANG J,CHEN K,XU R,et al.Carafe:Content-aware reassembly of features[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.2019:3007-3016. [24]SRINIVAS A,LIN T Y,PARMAR N,et al.Bottleneck transformers for visual recognition[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2021:16519-16529. [25]HE K,ZHANG X,REN S,et al.Deep residual learning forimage recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2016:770-778. [26]XIA G S,BAI X,DING J,et al.DOTA:A large-scale dataset for object detection in aerial images[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2018:3974-3983. [27]CHENG G,ZHOU P,HAN J.Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images[J].IEEE Transactions on Geoscience and Remote Sensing,2016,54(12):7405-7415. |
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