Gotowa bibliografia na temat „Sea clutter extraction”
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Artykuły w czasopismach na temat "Sea clutter extraction"
Zhang, Le, Anke Xue, Xiaodong Zhao, Shuwen Xu i Kecheng Mao. "Sea-Land Clutter Classification Based on Graph Spectrum Features". Remote Sensing 13, nr 22 (15.11.2021): 4588. http://dx.doi.org/10.3390/rs13224588.
Pełny tekst źródłaZhang, Ling, Wei You, Q. Wu, Shengbo Qi i Yonggang Ji. "Deep Learning-Based Automatic Clutter/Interference Detection for HFSWR". Remote Sensing 10, nr 10 (21.09.2018): 1517. http://dx.doi.org/10.3390/rs10101517.
Pełny tekst źródłaZhao, Di, Hongyan Xing, Haifeng Wang, Huaizhou Zhang, Xinyi Liang i Haoqi Li. "Sea-Surface Small Target Detection Based on Four Features Extracted by FAST Algorithm". Journal of Marine Science and Engineering 11, nr 2 (3.02.2023): 339. http://dx.doi.org/10.3390/jmse11020339.
Pełny tekst źródłaDuan, Guoxing, Yunhua Wang, Yanmin Zhang, Shuya Wu i Letian Lv. "A Network Model for Detecting Marine Floating Weak Targets Based on Multimodal Data Fusion of Radar Echoes". Sensors 22, nr 23 (25.11.2022): 9163. http://dx.doi.org/10.3390/s22239163.
Pełny tekst źródłaJiang, Yingqi, Lili Dong i Junke Liang. "Image Enhancement of Maritime Infrared Targets Based on Scene Discrimination". Sensors 22, nr 15 (5.08.2022): 5873. http://dx.doi.org/10.3390/s22155873.
Pełny tekst źródłaPan, Xueli, Nana Li, Lixia Yang, Zhixiang Huang, Jie Chen, Zhenhua Wu i Guoqing Zheng. "Anomaly-Based Ship Detection Using SP Feature-Space Learning with False-Alarm Control in Sea-Surface SAR Images". Remote Sensing 15, nr 13 (24.06.2023): 3258. http://dx.doi.org/10.3390/rs15133258.
Pełny tekst źródłaFarshchian, Masoud. "Target Extraction and Imaging of Maritime Targets in the Sea Clutter Spectrum Using Sparse Separation". IEEE Geoscience and Remote Sensing Letters 14, nr 2 (luty 2017): 232–36. http://dx.doi.org/10.1109/lgrs.2016.2636253.
Pełny tekst źródłaNingbo, Liu, Xu Yanan, Ding Hao, Xue Yonghua i Guan Jian. "High-dimensional feature extraction of sea clutter and target signal for intelligent maritime monitoring network". Computer Communications 147 (listopad 2019): 76–84. http://dx.doi.org/10.1016/j.comcom.2019.08.016.
Pełny tekst źródłaWu, Zheng Long, Jie Li i Zhen Yu Guan. "Feature Extraction of Underwater Target Ultrasonic Echo Based on Wavelet Transform". Applied Mechanics and Materials 599-601 (sierpień 2014): 1517–22. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1517.
Pełny tekst źródłaChen, Xiaolong, Jian Guan, Zhonghua Bao i You He. "Detection and Extraction of Target With Micromotion in Spiky Sea Clutter Via Short-Time Fractional Fourier Transform". IEEE Transactions on Geoscience and Remote Sensing 52, nr 2 (luty 2014): 1002–18. http://dx.doi.org/10.1109/tgrs.2013.2246574.
Pełny tekst źródłaRozprawy doktorskie na temat "Sea clutter extraction"
Michelet, Jordan. "Extraction du fouillis de mer dans des images radar marin cohérent : modèles de champ de phases, méthodes de Boltzmann sur réseau, apprentissage". Electronic Thesis or Diss., La Rochelle, 2022. http://www.theses.fr/2022LAROS048.
Pełny tekst źródłaWe focus on the problem of sea clutter extraction in marine radar images. The aim is to develop image processing methods allowing us to avoid assumptions about the nature of the sea clutter and the signal of interest. On the one hand, we propose an original algorithm based on a variational approach : a multiphase model with diffuse interface. The results obtained show that the algorithm is efficient when the signal of interest has a sufficiently large signal-to-clutter ratio. On the other hand, we focus on the implementation of lattice Boltzmann schemes for convection-diffusion problems with non-constant advection velocity and non-zero source term. We describe the computation of the consistency obtained by asymptotic analysis at the acoustic scale and with a multiple relaxation time collision operator, and study the stability of these schemes in a particular case. The obtained results show that the proposed schemes allow removing the residual noise and to enhance the signal of interest on the image obtained with the first method. Finally, we propose a learning method allowing us to avoid assumptions on the nature of the signal of interest. Indeed, in addition to the variational approach, we propose an algorithm based on pulse-Doppler processing when the signal of interest is exo-clutter and has a low signal-to-clutter ratio. The results obtained from the proposed double auto-encoder, being comparable to the results provided by each of the two methods, allow validating this approach
Streszczenia konferencji na temat "Sea clutter extraction"
Yuan, Xujin, Yong Chen, Chao Wang, Hongcheng Yin, Jingping Yao, Zhiming Xu i Yongge Lu. "A new correlation parameter extraction method for searching mode sea clutter restraint". W International Symposium on Optoelectronic Technology and Application 2014, redaktorzy Gaurav Sharma, Fugen Zhou i Jennifer Liu. SPIE, 2014. http://dx.doi.org/10.1117/12.2069459.
Pełny tekst źródłaLi, Yang, Xinyang Wang, Ning Zhang, Wenxing Wang, Qiming Zhang, Wenbo Ding i Longshan Wu. "A Machine Learning Based First-Order Sea Clutter Region Extraction Method for HFSWR". W 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. IEEE, 2019. http://dx.doi.org/10.1109/apusncursinrsm.2019.8888570.
Pełny tekst źródłaWu, Taifeng, Zhongtao Luo, Zishu He, Wang Zhaoyi i Xuyuan Chen. "Sea-clutter region extraction based on image segmentation methods for over-the-horizon radar". W 2018 IEEE Radar Conference (RadarConf18). IEEE, 2018. http://dx.doi.org/10.1109/radar.2018.8378590.
Pełny tekst źródłaWang, Yiwei, Bo Yin, Jinpeng Zhang i Yushi Zhang. "Effective Sea Clutter Region Extraction Based on Improved YOLOv4 Algorithm for Shore-Based UHF-Band Radar". W 2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ). IEEE, 2022. http://dx.doi.org/10.1109/iaeac54830.2022.9929877.
Pełny tekst źródłaThayaparan, Thayananthan, Milos Darkovic i Ljubisa Stankovic. "CFAR detection and extraction of maneuvering air target in strong sea-clutter via time-frequency-based S-method". W SPIE Defense, Security, and Sensing, redaktorzy Kenneth I. Ranney i Armin W. Doerry. SPIE, 2009. http://dx.doi.org/10.1117/12.819361.
Pełny tekst źródłaStory, W. Rob, Thomas C. Fu i Erin E. Hackett. "Radar Measurement of Ocean Waves". W ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49895.
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