Abstract: object detection; sonar image; attention; progressive perception; loss function[1] 汤寓麟, 李厚朴, 张卫东, 等. 侧扫声纳检测沉船目标的轻量化DETR-YOLO法[J]. 系统工程与电子技术, 2022, 44(8): 2427-2436. 
TANG Y L, LI H P, ZHANG W D, et al. Lightweight DETR-YOLO method for detecting shipwreck target in side-scan sonar[J]. Systems Engineering and Electronics, 2022, 44(8): 2427-2436. 
[2] 郭戈, 王兴凯, 徐慧朴. 基于声呐图像的水下目标检测、识别与跟踪研究综述[J]. 控制与决策, 2018, 33(5): 906-922. 
GUO G, WANG X K, XU H P. Review on underwater target detection, recognition and tracking based on sonar image[J]. Control and Decision, 2018, 33(5): 906-922. 
[3] 王强, 孟晨, 王成, 等. 基于分数阶Gabor变换的LFM回波信号压缩采样方法[J]. 系统工程与电子技术, 2022, 44(4): 1103-1112. 
WANG Q, MENG C, WANG C, et al. Compressive sampling method based on fractional Gabor transform for LFM echo signals[J]. Systems Engineering and Electronics, 2022, 44(4): 1103-1112. 
[4] LENG X G, JI K F, KUANG G Y. Ship detection from raw SAR echo data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5207811. 
[5] YAN Z L, CUI X W, GAO Y. Acoustic injection method based on weak echo signals for leak detection and localization in gas pipelines[J]. Applied Acoustics, 2023, 211: 109577.
[6] LANE D M, STONER J P. Automatic interpretation of sonar imagery using qualitative feature matching[J]. IEEE Journal of Oceanic Engineering, 1994, 19(3): 391-405. 
[7] MAUSSANG F, CHANUSSOT J, HETET A, et al. Mean-standard deviation representation of sonar images for echo detection: application to SAS images[J]. IEEE Journal of Oceanic Engineering, 2007, 32(4): 956-970. 
[8] TAO W L, LIU Y. Combined imaging matching method of side scan sonar images with prior position knowledge[J]. IET Image Processing, 2018, 12(2): 194-199. 
[9] 李庆武, 石丹, 霍冠英. 基于Contourlet变换的海底声纳图像特征提取与分类[J]. 海洋学报, 2011, 33(5): 163-168. 
LI Q W, SHI D, HUO G Y. Feature extraction and classification of seabed sonar Images Based on Contourlet transform[J]. Acta Oceanologica Sinica, 2011, 33(5): 163-168. 
[10] FAN Z M, XIA W J, LIU X, et al. Detection and segmentation of underwater objects from forward-looking sonar based on a modified Mask RCNN[J]. Signal, Image and Video Processing, 2021, 15(6): 1135-1143. 
[11] 刘扬, 田猛, 曹珂境, 等. 面向声呐图像水下目标分类的类脑SNN研究[J]. 计算机工程与应用, 2023, 59(10): 204-212.
LIU Y, TIAN M, CAO K J, et al. Research on brain-inspired SNN for underwater target classification of sonar images[J]. Computer Engineering and Applications, 2023, 59(10): 204-212.
[12] ZHU X Y, LIANG Y S, ZHANG J L, et al. STAFNet: swin transformer based anchor-free network for detection of forward-looking sonar imagery[C]//Proceedings of the 2022 International Conference on Multimedia Retrieval. New York: ACM, 2022: 443-450. 
[13] WANG Y M, LIU J X, YU S Q, et al. Underwater object detection based on YOLO-v3 network[C]//Proceedings of the 2021 IEEE International Conference on Unmanned Systems. Piscataway: IEEE, 2021: 571-575. 
[14] LI J W, CAO X. Target recognition and detection in side-scan sonar images based on YOLO v3 model[C]//Proceedings of the 2022 41st Chinese Control Conference. Piscataway: IEEE, 2022: 7186-7190. 
[15] GIRSHICK R. Fast R-CNN[C]//Proceedings of the 2015 IEEE International Conference on Computer Vision. Piscataway: IEEE, 2015: 1440-1448. 
[16] KIM J, CHOI J W, KWON H, et al. The application of convolutional neural networks for automatic detection of underwater object in side scan sonar images[J]. The Journal of the Acoustical Society of Korea, 2018, 37(2): 118-128. 
[17] 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. 
[18] XU Y C, WANG X M, WANG K H, et al. Underwater sonar image classification using generative adversarial network and convolutional neural network[J]. IET Image Processing, 2020, 14(12): 2819-2825. 
[19] 李书东. 基于深度学习的侧扫声呐条带图像沉船探测方法研究[D]. 连云港: 江苏海洋大学, 2022. 
LI S D. Research on shipwreck detection method from side-scan sonar image based on deep learning[D]. Lianyungang: Jiangsu Ocean University, 2022. 
[20] GE Z, LIU S T, WANG F, et al. YOLOX: exceeding YOLO series in 2021[J]. arXiv:2107.08430, 2021. 
[21] 李宝奇, 黄海宁, 刘纪元, 等. 基于改进SSD的合成孔径声呐图像水下多尺度目标轻量化检测模型[J]. 电子与信息学报, 2021, 43(10): 2854-2862. 
LI B Q, HUANG H N, LIU J Y, et al. Synthetic aperture sonar underwater multi-scale target efficient detection model based on improved single shot detector[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2854-2862.
[22] 陶洋, 朱腾, 钟邦乾, 等. RepViTS-YOLOX: 水下模糊及遮挡目标检测方法[J]. 计算机工程与应用, 2024, 60(13): 200-208. 
TAO Y, ZHU T, ZHONG B Q, et al. RepViTS-YOLOX: underwater blurred and occluded target detection method[J]. Computer Engineering and Applications, 2024, 60(13): 200-208.
[23] 辛世澳, 葛海波, 袁昊, 等. 改进YOLOv7的轻量化水下目标检测算法[J]. 计算机工程与应用, 2024, 60(3): 88-99. 
XIN S A, GE H B, YUAN H, et al. Improved lightweight underwater target detection algorithm of YOLOv7[J]. Computer Engineering and Applications, 2024, 60(3): 88-99. 
[24] 陈禹蒲, 马晓川, 李璇. 基于YOLOv3锚框优化的侧扫声呐图像目标检测[J]. 信号处理, 2022, 38(11): 2359-2371. 
CHEN Y P, MA X C, LI X. Target detection in side scan sonar images based on YOLOv3 anchor boxes optimization[J]. Journal of Signal Processing, 2022, 38(11): 2359-2371. 
[25] 汤寓麟, 边少锋, 翟国君, 等. 侧扫声呐检测沉船目标的改进YOLOv5法[J]. 武汉大学学报(信息科学版), 2024, 49(6): 977-985. 
TANG Y L, BIAN S F, ZHAI G J, et al. An improved YOLOv5 method for shipwreck target detection by side-scan sonar images[J]. Geomatics and Information Science of Wuhan University, 2024, 49(6): 977-985. 
[26] CHENG Z, HUO G Y, LI H S. A multi-domain collaborative transfer learning method with multi-scale repeated attention mechanism for underwater side-scan sonar image classification[J]. Remote Sensing, 2022, 14(2): 355. 
[27] 胡宏洋. 基于注意力感知的声呐图像轻量级目标检测网络研究[D]. 杭州: 杭州电子科技大学, 2022. 
HU H Y. Research on attention-aware lightweight target detection network for sonar images[D]. Hangzhou: Hangzhou Dianzi University, 2022. 
[28] HU J, SHEN L, SUN G. Squeeze-and-excitation networks[C]//Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2018: 7132-7141. 
[29] WOO S, PARK J, LEE J Y, et al. CBAM: convolutional block attention module[C]//Proceedings of the 15th European Conference on Computer Vision. Cham: Springer International Publishing, 2018: 3-19. 
[30] GE C J, DING X H, TONG Z, et al. Advancing vision transformers with group-mix attention[J]. arXiv:2311.15157, 2023.
[31] HUO G Y, WU Z Y, LI J B. Underwater object classification in sidescan sonar images using deep transfer learning and semisynthetic training data[J]. IEEE Access, 2020, 8: 47407-47418. 
[32] 周彦, 陈少昌, 吴可, 等. SCTD1.0: 声呐常见目标检测数据集[J]. 计算机科学, 2021, 48(S2): 334-339. 
ZHOU Y, CHEN S C, WU K, et al. SCTD 1.0: sonar common target detection dataset[J]. Computer Science, 2021, 48(S2): 334-339. 
[33] WANG Q L, WU B G, ZHU P F, et al. ECA-net: efficient channel attention for deep convolutional neural networks[C]//Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2020: 11531-11539. 
[34] HOU Q B, ZHOU D Q, FENG J S. Coordinate attention for efficient mobile network design[J]. arXiv:2103.02907, 2021.
[35] SELVARAJU R R, COGSWELL M, DAS A, et al. Grad-CAM: visual explanations from deep networks via gradient-based localization[J]. International Journal of Computer Vision, 2020, 128(2): 336-359.

摘要： 目标检测；声呐图像；注意力；渐进式感知；损失函数