Computer Science ›› 2025, Vol. 52 ›› Issue (6A): 240600118-8.doi: 10.11896/jsjkx.240600118
• Image Processing & Multimedia Technology • Previous Articles Next Articles
CHEN Tianpeng, HU Jianwen, LI Haitao
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| [1]NAN X H,DING L.A Review of Typical Target Detection Algorithms for Deep Learning[J].Computer Applications Research,2020,37(S2):15-21. [2]LIU J Q,LIU Z,ZHANG X Y.Review of Maritime Target Detection in Visible Bands of Optical Remote Sensing Images[J].Compute Science,2020,47(3):116-123. [3]CHEN T P,HU J W.Overview of deep learning for oriented ro-tating object detection in remote sensing images[J].Computer Applications Research,2024,41(2):329-340. [4]DING R L,LI J,ZHANG M.Ship Target Detection in Remote Sensing Image Based on S-HOG[J].Compute Science,2020,47(S2):248-252. [5]ZOU H X,KUANG G Y,YU W X.Detection of Ship Targetsfrom SAR ImageryBased on Feature Vector Matching[J].Mo-dern Radar,2004(8):25-29. [6]JIANG L B,WANG Z,HU W D.A ROI-based Infrared ShipTarget Detection Approach[J].Infrared Technology,2006(9):535-539. [7]YIN Y,HUANG H,ZHANG Z X.Research on Ship Detection Technology Based on Optical Remote Sensing Image[J].Compute Science,2019,46(3):82-87. [8]HUANG Z X,WU F L,FU Y.Review of deep learning-based algorithms forship target detection from remote sensing images[J].Optics and Precision Engineering,2023,31(15):2295-2318. [9]ZHAO Q C,WU Y Q,YUAN Y B.Research Progress of Ship Target Detection and Recognition Methods in Optical Remote Sensing Images[J].Chinese Journal of Aeronautics,2023,31(15):2295-2318. [10]WU W L,FANG J,WU Y.Small ship target YOLOv4detection based on improvedin complex scene[J].Transducer and Microsystem Technologies,2023,42(12):119-122. [11]BOCHKOVSKIY A,WANG C Y,LIAO H Y M.Yolov4:Optimal speed and accuracy of object detection[J].arXiv:2004.10934,2020. [12]ZHOU C Y.Analysis of Real time Remote Sensing Image ShipTarget Rotation Detection Algorithm for YOLOv7[J].Research and Design,2024,41(1):28-29. [13]WANG C Y,BOCHKOVSKIY A,LIAO H Y M.YOLOv7:Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2023:7464-7475. [14]LIU Y,SHAO Z,TENG Y,et al.NAM:Normalization-basedattention module[J].arXiv:2111.12419,2021. [15]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. [16]REN S,HE K,GIRSHICK R,et al.Faster r-cnn:Towards real-time object detection with region proposal networks[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2016,39(6):1137-1149. [17]XIE X X,CHENG G,WANG J B,et al.Oriented R-CNN for object detection [C]//Proceedings of the IEEE/CVF International Conference on Computer Vision.2021:3520-3529. [18]ZHOUG Q,HUANG L,SUN Q.Fine-grained detection method for remote sensing ship targets with improved Oriented R-CNN[J].Computer Engineering and Applications,2024,60(15):307-317. [19]SONG Z N,LI S,YANG J M,et al.Remote sensing ship target detection based on feature and region localization enhancement[J].Computer Engineering,2023,49(8):257-264. [20]CHE S W,WANG Y L.An Improved YOLOv7-Based Ship Target Detection Algorithm for Optical Remote Sensing Images[J].Electronics Optics & Control,2024,31(5):34-39,65. [21]LI C,ZHOU A,YAO A.Omni-dimensional dynamic convolution[J].arXiv:2209.07947,2022. [22]WANG X,WANG G,DANG Q,et al.PP-YOLOE-R:An efficient anchor-free rotated object detector[J].arXiv:2211.02386,2022. [23]ZHANG Q L,YANG Y B.Sa-net:Shuffle attention for deep convolutional neural networks[C]//ICASSP 2021－2021 IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP).IEEE,2021:2235-2239. [24]XU S,WANG X,LV W,et al.PP-YOLOE:An evolved version of YOLO[J].arXiv:2203.16250,2022. [25]LLERENA J M,ZENI L F,KRISTEN L N,et al.Gaussian bounding boxes and probabilistic intersection-over-union for object detection[J].arXiv:2106.06072,2021. [26]DING X,ZHANG X,MA N,et al.Repvgg:Making vgg-style convnets great again[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2021:13733-13742. [27]WANG C Y,LIAO H Y M,WU Y H,et al.CSPNet:A new backbone that can enhance learning capability of CNN[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops.2020:390-391. [28]SU S,WANG X,LV W,et al.PP-YOLOE:An evolved version of YOLO[J].arXiv:2203.16250,2022. [29]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. [30]LI X,WANG W,WU L,et al.Generalized focal loss:Learning qualified and distributed bounding boxes for dense object detection[J].Advances in Neural Information Processing Systems,2020,33:21002-21012. [31]LIU Z,YUAN L,WENG L,et al.A high resolution optical satellite image dataset for ship recognition and some new baselines[C]//ICPRAM.2017:324-331. [32]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. [33]LI W,CHEN Y,HU K,et al.Oriented reppoints for aerial object detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2022:1829-1838. [34]ZHOU Y,YANG X,ZHANG G,et al.Mmrotate:A rotated object detection benchmark using pytorch[C]//Proceedings of the 30th ACM International Conference on Multimedia.2022:7331-7334. [35]CHEN T P,HU J W.Ships Detection in Remote Sensing Images Based on Improved FCOS[J/OL].https://www.jsjkx.com/CN/article/openArticlePDF.jsp?id=22451. [36]GAO L,GAO H,WANG Y,et al.Center-Ness and Repulsion:Constraints to Improve Remote Sensing Object Detection via RepPoints[J].Remote Sensing,2023,15(6):1479. [37]GUO Z,LIU C,ZHANG X,et al.Beyond bounding-box:Con-vex-hull feature adaptation for oriented and densely packed object detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.2021:8792-8801. |
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