[1] Chen X Y, Lu Y, Wu Z X et al. Reveal of domain effect: how visual restoration contributes to object detection in aquatic scenes[EB/OL]. https://arxiv.org/abs/2003.01913

[2] Lin S, Zhao Y. Review on key technologies of target exploration in underwater optical images[J]. Laser & Optoelectronics Progress, 57, 060002(2020).

[3] Boom B J, Huang P X, He J Y et al. Supporting ground-truth annotation of image datasets using clustering[C], 1542-1545(2012).

[4] Chen H J, Bai H R. Subspace projection based track-before-detect scheme for small moving target in complex underwater environment[J]. Journal of Electronics & Information Technology, 43, 826-833(2021).

[5] Zhao Y Q, Rao Y, Dong S P et al. Survey on deep learning object detection[J]. Journal of Image and Graphics, 25, 629-654(2020).

[6] 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, 39, 1137-1149(2016).

[7] Liu W, Anguelov D, Erhan D et al. SSD: single shot multibox detector[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9905, 21-37(2016).

[8] Liu S T, Huang D, Wang Y H. Receptive field block net for accurate and fast object detection[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11215, 404-419(2018).

[9] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection[C], 779-788(2016).

[10] Redmon J, Farhadi A. YOLOv3: an incremental improvement[EB/OL]. https://arxiv.org/abs/1804.02767

[11] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

[12] Tan M X, Pang R M, Le Q V. EfficientDet: scalable and efficient object detection[C], 10781-10790(2020).

[13] Zheng Y L, Gong Q Y, Zhang S F. Time-frequency feature-based underwater target detection with deep neural network in shallow sea[J]. Journal of Physics: Conference Series, 1756, 012006(2021).

[14] Zhang Y B, Guo W, Zhou Y et al. Real-time target detection of underwater relics based on multigranularity pruning[J]. Laser & Optoelectronics Progress, 58, 1410019(2021).

[15] Guan J G, Zhao Y, Zheng Y Q et al. Optical polarization imaging for underwater target detection with non-scatter background[J]. Journal of Measurement Science and Instrumentation, 335-342(2020).

[16] Zhang D, Kopanas G, Desai C et al. Unsupervised underwater fish detection fusing flow and objectiveness[C](2016).

[17] Mandal R, Connolly R M, Schlacher T A et al. Assessing fish abundance from underwater video using deep neural networks[C](2018).

[18] Rathi D, Jain S, Indu S. Underwater fish species classification using convolutional neural network and deep learning[C](2017).

[19] Chen L, Zhou F X, Wang S K et al. SWIPENET: object detection in noisy underwater images[EB/OL]. https://arxiv.org/abs/2010.10006

[20] Lin W H, Zhong J X, Liu S et al. ROIMIX: proposal-fusion among multiple images for underwater object detection[C], 2588-2592(2020).

[21] Han F L, Yao J Z, Zhu H T et al. Underwater image processing and object detection based on deep CNN method[J]. Journal of Sensors, 2020, 6707328(2020).

[22] Zhou W, Tang H L, Li G D et al. DDAT target tracking algorithm based on occlusion detection mechanism[J]. Laser & Optoelectronics Progress, 57, 241501(2020).

[23] Liu K W, Ma Y, Xiong H X et al. Medical-image super-resolution reconstruction method based on residual channel attention network[J]. Laser & Optoelectronics Progress, 57, 021014(2020).