• Electronics Optics & Control
  • Vol. 32, Issue 4, 17 (2025)
HUANG Yingzheng1, LIU Gang2, YAN Shuguang1, and HOU Enxiang1
Author Affiliations
  • 1School of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210000, China
  • 2School of Electronics and Information Engineering, Wuxi University, Wuxi 214000, China
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    DOI: 10.3969/j.issn.1671-637x.2025.04.003 Cite this Article
    HUANG Yingzheng, LIU Gang, YAN Shuguang, HOU Enxiang. An SAR Ship Detection Algorithm Based on Receptive Field Enhancement and Cross-Scale Fusion[J]. Electronics Optics & Control, 2025, 32(4): 17 Copy Citation Text show less
    References

    [3] REN S Q, HE K M, 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, 2017, 39(6): 1137-1149.

    [4] LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multibox detector[R]. Los Alamos: arXiv Preprint, 2016: arXiv: 1512. 02325.

    [5] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, real-time object detection[C]//IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Las Vegas: IEEE, 2016: 779-788.

    [8] KE X, ZHANG X L, ZHANG T W, et al. SAR ship detection based on an improved Faster R-CNN using deformable convolution[C]//IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Brussels: IEEE, 2021: 3565-3568.

    [9] LIU Y, WANG X Q. SAR ship detection based on improved YOLOv7-tiny[C]//IEEE 8th International Conference on Computer and Communications (ICCC). Chengdu: IEEE, 2022: 2166-2170.

    [10] ZHANG L L, LIU Y X, QU L L, et al. A spatial cross-scale attention network and global average accuracy loss for SAR ship detection[J]. Remote Sensing, 2023, 15(2): 350.

    [11] ZHAO C X, FU X J, DONG J, et al. LPDNet: a lightweight network for SAR ship detection based on multi-level Laplacian denoising[J]. Sensors, 2023, 23(13): 6084.

    [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]//IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR). Vancouver: IEEE, 2023: 7464-7475.

    [15] HUANG L, CHEN C, YUN J T, et al. Multi-scale feature fusion convolutional neural network for indoor small target detection[J]. Frontiers in Neurorobotics, 2022, 16: 881021.

    [16] CHEN J R, KAO S-H, HE H, et al. Run, don't walk: chasing higher FLOPS for faster neural networks[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR). Vancouver: IEEE, 2023: 12021-12031.

    [17] HOU Q B, ZHOU D Q, FENG J S. Coordinate attention for efficient mobile network design[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Nashville: IEEE, 2021: 13713-13722.

    [18] ZHANG X, LIU C, YANG D G, et al. RFAConv: innovating spatital attention and standard convolutional operation[R]. Los Alamos: arXiv Preprint, 2023: arXiv: 2304. 03198.

    [19] MA S L, XU Y. MPDIoU: a loss for efficient and accurate bounding box regression[R]. Los Alamos: arXiv Preprint, 2023: arXiv: 2307. 07662.

    [20] ZHANG H, ZHANG S J. Focaler-IoU: more focused intersection over union loss[R]. Los Alamos: arXiv Preprint, 2024: arXiv: 2401. 10525.

    [21] WEI S J, ZENG X F, QU Q Z, et al. HRSID: a high-resolution SAR images dataset for ship detection and instance segmentation[J]. IEEE Access, 2020, 8: 120234-120254.

    [22] DUAN K W, BAI S, XIE L X, et al. CenterNet: keypoint triplets for object detection[C]//IEEE/CVF International Conference on Computer Vision(ICCV). Seoul: IEEE, 2019: 6569-6578.

    HUANG Yingzheng, LIU Gang, YAN Shuguang, HOU Enxiang. An SAR Ship Detection Algorithm Based on Receptive Field Enhancement and Cross-Scale Fusion[J]. Electronics Optics & Control, 2025, 32(4): 17
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