Systems Engineering and Electronics ›› 2022, Vol. 44 ›› Issue (12): 3652-3660.doi: 10.12305/j.issn.1001-506X.2022.12.08
• Sensors and Signal Processing • Previous Articles Next Articles
Yu LEI, Xiangguang LENG*, Xiaoyan ZHOU, Zhongzhen SUN, Kefeng JI
Received:
2021-06-28
Online:
2022-11-14
Published:
2022-11-24
Contact:
Xiangguang LENG
CLC Number:
Yu LEI, Xiangguang LENG, Xiaoyan ZHOU, Zhongzhen SUN, Kefeng JI. Recognition method of ship target in complex SAR image based on improved ResNet network[J]. Systems Engineering and Electronics, 2022, 44(12): 3652-3660.
Table 2
Experimental results of implicit complex information enhancement in the input layer"
网络模型 | 数据类型 | 精确率 | 准确率 | |
货船 | 油船 | |||
VGG16Net | Z1 | 0.727 | 0.730 | 0.727 |
VGG16Net | Z2 | 0.722 | 0.736 | 0.730 |
VGG16Net | Z3 | 0.732 | 0.768 | 0.739 |
VGG16Net | Z4 | 0.736 | 0.709 | 0.722 |
GoogLeNet | Z1 | 0.707 | 0.697 | 0.697 |
GoogLeNet | Z2 | 0.709 | 0.722 | 0.713 |
GoogLeNet | Z3 | 0.722 | 0.736 | 0.727 |
GoogLeNet | Z4 | 0.729 | 0.691 | 0.713 |
ResNet18 | Z1 | 0.703 | 0.80 | 0.739 |
ResNet18 | Z2 | 0.744 | 0.753 | 0.750 |
ResNet18 | Z3 | 0.753 | 0.786 | 0.772 |
ResNet18 | Z4 | 0.760 | 0.750 | 0.759 |
1 | 冷祥光, 计科峰, 熊博莅, 等. 面向舰船目标检测的单通道复值SAR图像统计建模方法研究[J]. 雷达学报, 2020, 9 (3): 477- 496. |
LENG X G , JI K F , XIONG B L , et al. Statistical modeling methods of single channel complex-valued SAR images for ship detection[J]. Journal of Radars, 2020, 9 (3): 477- 496. | |
2 | 杜兰, 王兆成, 王燕, 等. 复杂场景下单通道SAR目标检测及鉴别研究进展综述[J]. 雷达学报, 2020, 9 (1): 34- 54. |
DU L , WANG Z C , WANG Y , et al. Survey of research progress on target detection and discrimination of single-channel SAR images for complex scenes[J]. Journal of Radars, 2020, 9 (1): 34- 54. | |
3 | 雷禹, 冷祥光, 计科峰. 基于Google Earth Engine的海量舰船目标SAR图像处理应用研究[J]. 信号处理, 2021, 37 (6): 1075- 1085. |
LEI Y , LENG X G , JI K F . Research on the application of SAR image processing of massive ship targets based on Google Earth Engine[J]. Journal of Signal Processing, 2021, 37 (6): 1075- 1085. | |
4 | 张荻. 基于深度学习的SAR图像舰船目标识别方法研究[D]. 长沙: 国防科技大学, 2017. |
ZHANG D. Study on recognition of ships in SAR imagery based on deep learning methods[D]. Changsha: National University of Defense Technology, 2017. | |
5 | 康妙. 基于深度学习的SAR图像舰船目标检测与识别技术研究[D]. 长沙: 国防科技大学, 2017. |
KANG M. Study on the methods of SAR ship detection and recognition based on deep learning[D]. Changsha: National University of Defense Technology, 2017. | |
6 |
李家起, 江政杰, 姚力波, 等. 一种基于深度学习的舰船目标融合识别算法[J]. 舰船电子工程, 2020, 40 (9): 31- 35. 31-35, 171
doi: 10.3969/j.issn.1672-9730.2020.09.008 |
LI J Q , JIANG Z J , YAO L B , et al. A ship target fusion recognition algorithm based on deep learning[J]. Ship Electronic Engineering, 2020, 40 (9): 31- 35. 31-35, 171
doi: 10.3969/j.issn.1672-9730.2020.09.008 |
|
7 |
MARGARIT G , MALLORQUI J J , FABREGAS X . Single-pass polarimetric SAR interferometry for vessel classification[J]. IEEE Trans.on Geoscience and Remote Sensing, 2007, 45 (11): 3494- 3502.
doi: 10.1109/TGRS.2007.897437 |
8 |
PALADIN R , MARTORELL M , BERIZZI F . Classification of man-made targets via invariant coherency-matrix eigenvector decomposition of polarimetric SAR/ISAR images[J]. IEEE Trans.on Geoscience and Remote Sensing, 2011, 49 (8): 3022- 3034.
doi: 10.1109/TGRS.2011.2116121 |
9 |
HINTON G E , SALAKHUTDINOV R R . Reducing the dimensionality of data with neural networks[J]. Science, 2006, 313 (5786): 504- 507.
doi: 10.1126/science.1127647 |
10 |
邵嘉琦, 曲长文, 李健伟, 等. 基于CNN的不平衡SAR图像舰船目标识别[J]. 电光与控制, 2019, 26 (9): 90- 97.
doi: 10.3969/j.issn.1671-637X.2019.09.019 |
SHAO J Q , QU C W , LI J W , et al. CNN based ship target recognition of imbalanced SAR image[J]. Electronics Optics & Control, 2019, 26 (9): 90- 97.
doi: 10.3969/j.issn.1671-637X.2019.09.019 |
|
11 |
LI L L , MA L Y , JIAO L C , et al. Complex contourlet-CNN for polarimetric SAR image classification[J]. Pattern Recognition, 2020, 100, 107110.
doi: 10.1016/j.patcog.2019.107110 |
12 | 李玲玲. 量子进化优化与深度复神经网络学习算法及其应用[D]. 西安: 西安电子科技大学, 2017. |
LI L L. Quantum evolutional optimization and deep complex neural networks learning[D]. Xi'an: Xidian University, 2017. | |
13 |
LECUN Y , BENGIO Y , HINTON G . Deep learning[J]. Nature, 2015, 521 (7553): 436- 444.
doi: 10.1038/nature14539 |
14 | DONAHUE J, HENDRICKS L A, GUADARRAMD S, et al. Long-term recurrent convolutional networks for visual recognition and description[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2015: 2625-2634. |
15 |
HINTON G , DENG L , YU D , et al. Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups[J]. IEEE Signal Processing Magazine, 2012, 29 (6): 82- 97.
doi: 10.1109/MSP.2012.2205597 |
16 |
EL-DARYMLI K , MCGUIRE P , GILL E W , et al. Characterization and statistical modeling of phase in single-channel synthetic aperture radar imagery[J]. IEEE Trans.on Aerospace and Electronic Systems, 2015, 51 (3): 2071- 2092.
doi: 10.1109/TAES.2015.140711 |
17 | EL-DARYMLI K, MOLONEY C, GILL E, et al. Nonlinearity and the effect of detection on single-channel synthetic aperture radar imagery[C]//Proc. of the IEEE OCEANS, 2014. |
18 | 刘国祥. SAR成像原理与图像特征[J]. 四川测绘, 2004, 27 (3): 141- 143. |
LIU G X . Principles of imaging SAR and characteristics of image[J]. Surveying and Mapping of Sichuan, 2004, 27 (3): 141- 143. | |
19 | HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2016: 770-778. |
20 | 刘家麒, 陈渤, 介茜. 基于注意力机制和双向GRU模型的雷达HRRP目标识别[J]. 雷达学报, 2019, 8 (5): 589- 597. |
LIU J Q , CHEN B , JIE X . Radar high-resolution range profile target recognition based on attention mechanism and bidirectional gated recurrent[J]. Journal of Radars, 2019, 8 (5): 589- 597. | |
21 | 赵文清, 程幸福, 赵振兵, 等. 注意力机制和Faster RCNN相结合的绝缘子识别[J]. 智能系统学报, 2020, 15 (1): 92- 98. |
ZHAO W Q , CHENG X F , ZHAO Z B , et al. Insulator recognition based on attention mechanism and Faster RCNN[J]. CAAI Transactions on Intelligent Systems, 2020, 15 (1): 92- 98. | |
22 | 应自炉, 宣晨, 翟懿奎, 等. 面向小样本SAR图像识别的自注意力多尺度特征融合网络[J]. 信号处理, 2020, 36 (11): 1846- 1858. |
YING Z L , XUAN C , ZHAI Y K , et al. Self-attention multiscale feature fusion network for small sample SAR image recognition[J]. Journal of Signal Processing, 2020, 36 (11): 1846- 1858. | |
23 | HU J, SHEN L, SUN G. Squeeze-and-excitation networks[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2018: 7132-7141. |
24 | SZEGEDY C, VANHOUCKE V, IOFFE S, et al. Rethinking the inception architecture for computer vision[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2016: 2818-2826. |
25 | HE T, ZHANG Z, ZHANG H, et al. Bag of tricks for image classification with convolutional neural networks[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2019: 558-567. |
26 | MULLER R, KORNBLITH S, HINTON G E. When does label smoothing help?[C]//Proc. of the 33rd International Conference on Neural Information Processing Systems, 2019, 422: 4694-4703. |
27 | HUANG L Q , LIU B , LI B Y , et al. OpenSARShip: a dataset dedicated to Sentinel-1 ship interpretation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 11 (1): 195- 208. |
28 | LI B Y, LIU B, HUANG L Q, et al. OpenSARShip 2.0: a large-volume dataset for deeper interpretation of ship targets in Sentinel-1 imagery[C]//Proc. of the IEEE SAR in Big Data Era: Models, Methods and Applications, 2017: 1-5. |
29 | 赵楠, 张小芳, 张利军. 不平衡数据分类研究综述[J]. 计算机科学, 2018, 45 (B6): 22- 27. 22-27, 57 |
ZHAO N , ZHANG X F , ZHANG L J . Overview of imbalanced data classification[J]. Computer Science, 2018, 45 (B6): 22- 27. 22-27, 57 | |
30 | 李海涛. 基于深度学习的图像识别鲁棒性研究[D]. 南京: 南京邮电大学, 2018. |
LI H T. Research on image recognition robustness based on depth learning[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2018. |
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