Chinese Journal of Ship Research, Volume. 20, Issue 3, 305(2025)
Detection of water surface targets based on improved Deformable DETR
[6] [6] GIRSHICK R. Fast RCNN[C]2015 IEEE International Conference on Computer Vision. Santiago, Chile: IEEE, 2015: 1440−1448.
[7] [7] REN S Q, HE K M, GIRSHICK R, et al. Faster RCNN: Towards realtime object detection with region proposal wks[C]Proceedings of the 28th International Conference on Neural Infmation Processing Systems. Montreal: MIT Press, 2015: 91−99.
[9] [9] LIU W, ANGUELOV D, ERHAN D, et al. SSD: Single shot MultiBox detect[C]14th European Conference on Computer Vision–ECCV 2016. Amsterdam: Springer International Publishing, 2016: 21−37.
[10] [10] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, realtime object detection[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. Las Vegas: IEEE, 2016: 779−788.
[15] [15] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need[C]Proceedings of the 31st International Conference on Neural Infmation Processing Systems. Long Beach: Curran Associates Inc. , 2017: 6000−6010.
[16] [16] CARION N, MASSA F, SYNNAEVE G, et al. Endtoend object detection with transfmers[C]16th European Conference on Computer VisionECCV 2020. Cham: Springer International Publishing, 2020: 213−229.
[17] [17] ZHU X Z, SU W J, LU L W, et al. Defmable DETR: defmable transfmers f endtoend object detection[C]9th International Conference on Learning Representations. Virtual Event, Austria: ICLR, 2021.
[19] [19] DAI J F, QI H Z, XIONG Y W, et al. Defmable convolutional wks[C]Proceedings of the IEEE International Conference on Computer Vision. Venice: IEEE, 2017: 764−773.
[20] [20] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning f image recognition[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. Las Vegas: IEEE, 2016: 770−778.
[21] [21] HOWARD A, SLER M, CHEN B, et al. Searching f MobileV3[C]Proceedings of the IEEECVF International Conference on Computer Vision. Seoul: IEEE, 2019: 1314−1324.
[22] [22] HOWARD A G, ZHU M L, CHEN B, et al. Mobiles: efficient convolutional neural wks f mobile vision applications[JOL]. arXiv preprint arXiv: 1704.04861 (20170417) [20240106]. https:doi.g10.48550arXiv.1704.04861.
[23] [23] SLER M, HOWARD A, ZHU M L, et al. MobileV2: inverted residuals linear bottlenecks[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. Salt Lake City: IEEE, 2018: 4510−4520.
[24] [24] HU J, SHEN L, SUN G. Squeezeexcitation wks[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition. Salt Lake City: IEEE, 2018: 7132−7141.
[25] [25] WOO S, PARK J, LEE J Y, et al. CBAM: Convolutional block attention module[C]Proceedings of the 15th European Conference on Computer Vision (ECCV). Munich: Springer, 2018: 3−19.
[26] [26] REDMON J, FARHADI A. YOLOv3: an incremental improvement[JOL]. arXiv preprint arXiv: 1804.02767 (20180408) [20240106]. https:doi.g10.48550arXiv.1804.02767.
[27] [27] WANG C Y, BOCHKOVSKIY A, LIAO H Y M. YOLOv7: Trainable bagoffreebies sets new stateoftheart f realtime object detects[C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition. Vancouver: IEEE, 2023: 7464−7475.
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Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO. Detection of water surface targets based on improved Deformable DETR[J]. Chinese Journal of Ship Research, 2025, 20(3): 305
Category: Weapon, Electronic and Information System
Received: Nov. 14, 2023
Accepted: --
Published Online: Jul. 15, 2025
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