Zobrazeno 1 - 10
of 373
pro vyhledávání: '"Huaping XU"'
Publikováno v:
Leida xuebao, Vol 13, Iss 6, Pp 1327-1336 (2024)
The performance of Synthetic Aperture Radar (SAR) active deception jamming detection based on the interferometric phase is analyzed. Based on the slant-range local fringe frequency probability distributions of a real scene and a false target, the inf
Externí odkaz:
https://doaj.org/article/15ed1ecc39d847fbb63fe734638d7dd9
Publikováno v:
Remote Sensing, Vol 16, Iss 18, p 3487 (2024)
Ship wake detection stands as a pivotal task in marine environment monitoring. The main challenge in ship wake detection is to improve detection accuracy and mitigate false alarms. To address this challenge, a novel procedure for ship wake detection
Externí odkaz:
https://doaj.org/article/034abd907ddc4d7aac7f6e0844d68ccf
Publikováno v:
Advanced Science, Vol 10, Iss 31, Pp n/a-n/a (2023)
Abstract Visualizing polymer chain growth is always a hot topic for tailoring structure‐function properties in polymer chemistry. However, current characterization methods are limited in their ability to differentiate the degree of polymerization i
Externí odkaz:
https://doaj.org/article/f7802270a0dd4894903cd7d9c9eaab07
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 10007-10021 (2023)
Multipolarimetric synthetic aperture radar (SAR) interferometric phase optimization and phase series estimation have received a lot of attentions recently from the polarimetry SAR interferometry (PolInSAR) community. In this article, a maximum likeli
Externí odkaz:
https://doaj.org/article/c6ac7c5112ba4732820589d0d446b258
Publikováno v:
Remote Sensing, Vol 15, Iss 20, p 4941 (2023)
For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—who
Externí odkaz:
https://doaj.org/article/23e92371468b4cf69f7b35853ae7ed3e
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract In this study, we observed that four congeners, including naphthalene (Nap), acenaphthylene (Acy), phenanthrene (Phe), and benz(a)anthracene (BaA), are the characteristic congeners for predicting the emission and the sediment concentrations
Externí odkaz:
https://doaj.org/article/52fa34587a6448fab3c5fc33e408091a
Publikováno v:
Brazilian Journal of Pharmaceutical Sciences, Vol 58 (2023)
Abstract Cerebrovascular disease is the second most serious disease in the world. It has the features of high morbidity, high mortality and recurrence rate. Numerous research on the compatibility of Chinese medicine with effective ingredients of cere
Externí odkaz:
https://doaj.org/article/8baf8f3ea3b7410baebffd65955eacda
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
Background: Lung adenocarcinoma (LUAD) is a sex-biased and easily metastatic malignant disease. A signature based on 5 long non-coding RNAs (lncRNAs) has been established to promote the overall survival (OS) prediction effect on LUAD.Methods: The RNA
Externí odkaz:
https://doaj.org/article/35632bacf4cd4f37aeeeb9fd31abcfa4
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 9756-9767 (2021)
Phase noise reduction is one of the key steps for synthetic aperture radar interferometry data processing. In this article, a novel phase filtering method is proposed. The main innovation and contribution of this research is to 1) incorporate local f
Externí odkaz:
https://doaj.org/article/2f30631c2fe94c668b71b48331232fcf
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 10571-10582 (2021)
Layover detection has long been the focus of attention for interferometric synthetic aperture radar (InSAR) data processing. As for the existing layover detection methods, most of them are applied to single-baseline scenarios. Since multibaseline InS
Externí odkaz:
https://doaj.org/article/a965366a0bfe4bbd95289401050cbca4