[1] WANG F. Research on the situation and tasks of building a strong maritime power in the new era[J]. Journal of Ocean University of China (Social Sciences), 11-19(2020).

[2] CLAY C S, HORNE J K. Acoustic models of fish: the Atlantic cod (Gadus morhua)[J]. The Journal of the Acoustical Society of America, 96, 1661-1668(1994).

[3] HARLEY H E, DELONG C M. Echoic object recognition by the bottlenose dolphin[J]. Comparative Cognition & Behavior Reviews, 3, 46-65(2008).

[4] [4] TAN Y Q. Research on detection technology of underwater ferromagic target based on DC superconducting quantum interference device[D]. Changsha: National University of Defense Technology, 2020. (in Chinese).

[5] CHEN ZH X, LU J J. Current development of weak magnetic detection[J]. Mine Warfare & Ship Self-Defence, 19, 1-5,24(2011).

[6] XU W H, YANG J M, WEI H D et al. A localization algorithm based on pose graph using Forward-looking sonar for deep-sea mining vehicle[J]. Ocean Engineering, 284, 114968(2023).

[7] LUO Y H. Sonar image object detection system based on deep learning[J]. Digital Ocean & Underwater Warfare, 6, 423-428(2023).

[8] ISHAK A B. A two-dimensional multilevel thresholding method for image segmentation[J]. Applied Soft Computing, 52, 306-322(2017).

[9] ZHANG B M, ZHOU T, SHI ZI F et al. An underwater small target boundary segmentation method in forward-looking sonar images[J]. Applied Acoustics, 207, 109341(2023).

[10] [10] WAN G N. Research on underwater target detection based laser ultrasound[D]. Harbin: Harbin Institute of Technology, 2017. (in Chinese).

[11] ZHAI H X, JIANG Z L, ZHANG P F. Object segmentation method for synthetic aperture sonar images[J]. Chinese Journal of Scientific Instrument, 37, 887-894(2016).

[12] YANG W D, YE CH B, CHEN ZH L. Image contour extraction method based on snake algorithm[J]. Piezoelectrics & Acoustooptics, 45, 752-758(2023).

[13] [13] HU G. Research on underwater target recognition motion behavi analysis technology based on deep learning[D]. Harbin: Harbin Engineering University, 2021. (in Chinese).

[14] [14] DIVYABARATHI G, SHAILESH S, JUDY M V. Object classification in underwater SONAR images using transfer learning based ensemble model[C]. Proceedings of 2021 International Conference on Advances in Computing Communications, IEEE, 2021: 14.

[15] CHANDRASHEKAR G, RAAZA A, RAJENDRAN V et al. Side scan sonar image augmentation for sediment classification using deep learning based transfer learning approach[J]. Materials Today: Proceedings, 80, 3263-3273(2023).

[16] KONG W Z, HONG J CH, JIA M Y et al. YOLOv3-DPFIN: a dual-path feature fusion neural network for robust real-time sonar target detection[J]. IEEE Sensors Journal, 20, 3745-3756(2020).

[17] ZHAO L, LI S. Object detection algorithm based on improved YOLOv3[J]. Electronics, 9, 537(2020).

[18] FAN X N, LU L, SHI P F et al. A novel sonar target detection and classification algorithm[J]. Multimedia Tools and Applications, 81, 10091-10106(2022).

[19] [19] WANG C Y, Bochkovskiy A, Liao H Y M. Scaledyolov4: Scaling cross stage partial wk[C]Proceedings of the IEEEcvf conference on computer vision pattern recognition. 2021: 1302913038.

[20] GERG I D, MONGA V. Structural prior driven regularized deep learning for sonar image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 4200416(2022).

[21] NANDHINI S, ASHOKKUMAR K. An automatic plant leaf disease identification using DenseNet-121 architecture with a mutation-based henry gas solubility optimization algorithm[J]. Neural Computing and Applications, 34, 5513-5534(2022).

[22] [22] ZHU X Y, LIANG Y SH, ZHANG J L, et al. STAF: swin transfmer based anchfree wk f detection of fwardlooking sonar imagery[C]. Proceedings of the 2022 International Conference on Multimedia Retrieval, ACM, 2022: 443450.

[23] [23] LIU Z, LIN Y T, CAO Y, et al. Swin transfmer: hierarchical vision transfmer using shifted windows[C]. Proceedings of 2021 IEEECVF International Conference on Computer Vision, IEEE, 2021: 1001210022.

[24] LIU Y L, LI M ZH, WANG X X. Lightweight YOLOv5s vehicle infrared image target detection[J]. Chinese Optics, 16, 1045-1055(2023).

[25] ZHU W, WANG L K, JIN Z B. Lightweight small object detection network with attention mechanism[J]. Optics and Precision Engineering, 30, 998-1010(2022).

[26] QIAO M Y, SHI J K, LI B F. Enhanced FPN underwater small target detection with improved loss function[J]. Journal of Computer-Aided Design & Computer Graphics, 35, 525-537(2023).

[27] ZHANG Y, LI X SH, SUN Y M. Underwater object detection algorithm based on channel attention and feature fusion[J]. Journal of Northwestern Polytechnical University, 40, 433-441(2022).

[28] LI L, LI Y P, YUE CH H et al. Real-time underwater target detection for AUV using side scan sonar images based on deep learning[J]. Applied Ocean Research, 138, 103630(2023).

[29] [29] WANG C Y, BOCHKOVSKIY A, LIAO H Y M. YOLOv7: trainable bagoffreebies sets new stateoftheart f realtime object detects[C]. Proceedings of 2023 IEEECVF Conference on Computer Vision Pattern Recognition, IEEE, 2023: 74647475.

[30] ZHANG SH W, SHI W Y, ZHANG SH Q. Remote sensing small target detection based on weighted receptive field and cross-layer fusion[J]. Electronic Measurement Technology, 46, 129-138(2023).

[31] CUI L SH, LV P, JIANG X H et al. Context-aware block net for small object detection[J]. IEEE Transactions on Cybernetics, 52, 2300-2313(2022).

[32] Chen Y, Guo Q, Liang X et al. Environmental sound classification with dilated convolutions[J]. Applied Acoustics, 148, 123-132(2019).

[33] [33] WANG C Y, LIAO H Y M, WU Y H, et al. CSP: a new backbone that can enhance learning capability of CNN[C]. Proceedings of 2020 IEEECVF Conference on Computer Vision Pattern Recognition Wkshops, IEEE, 2020: 390391.

[34] XIE K, YANG J, QIU K. A dataset with multibeam forward-looking sonar for underwater object detection[J]. Scientific Data, 9, 739(2022).

[35] LIU Y, LIU H Y, FAN J L. A survey of research and application of small object detection based on deep learning[J]. Acta Electronica Sinica, 48, 590-601(2020).

[36] [36] CHEN CH Y, LIU M Y, TUZEL O, et al. RCNN f small object detection[C]. Proceedings of the 13th Asian Conference on Computer Vision, Springer, 2017: 214230.

[37] GAO X B, MO M J CH, WANG H T. Recent advances in small object detection[J]. Journal of Data Acquisition and Processing, 36, 391-417(2021).

[38] [38] LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot MultiBox detect[C]. Proceedings of the 14th European Conference, Springer, 2016: 2137.

[39] WANG Y Y, WANG CH, ZHANG H et al. Automatic ship detection based on RetinaNet using multi-resolution Gaofen-3 imagery[J]. Remote Sensing, 11, 531(2019).

[40] WU W, LIU H, LI L et al. Application of local fully convolutional neural network combined with YOLO v5 algorithm in small target detection of remote sensing image[J]. PloS one, 16, e0259283(2021).

[41] REN SH 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, 39, 1137-1149(2017).

[42] Dewi C, Chen A P S, Christanto H J. Recognizing similar musical instruments with YOLO models[J]. Big Data and Cognitive Computing, 7, 94(2023).

[43] HUSSAIN M. YOLO-v1 to YOLO-v8, the rise of YOLO and its complementary nature toward digital manufacturing and industrial defect detection[J]. Machines, 11, 677(2023).

[44] WU Q, ZHANG B, XU CH G et al. Dense oil tank detection and classification via YOLOX-TR network in large-scale SAR images[J]. Remote Sensing, 14, 3246(2022).

[45] MA L, ZHAO L Y, WANG Z X et al. Detection and counting of small target apples under complicated environments by using improved YOLOv7-tiny[J]. Agronomy, 13, 1419(2023).