Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Zide Fan"'
Publikováno v:
Sensors, Vol 24, Iss 20, p 6708 (2024)
In this study, we propose a practical and efficient scheme for ship detection in remote sensing imagery. Our method is developed using both ship body detection and ship wake detection and combines deep learning and feature-based image processing. A d
Externí odkaz:
https://doaj.org/article/6ab7bef0014b412b8f1f782ce5da51f1
Publikováno v:
Remote Sensing, Vol 16, Iss 3, p 600 (2024)
Ship detection in remote sensing images plays an important role in maritime surveillance. Recently, convolution neural network (CNN)-based methods have achieved state-of-the-art performance in ship detection. Even so, there are still two problems tha
Externí odkaz:
https://doaj.org/article/453cf78913954875a4590db49086813b
Publikováno v:
Sensors, Vol 24, Iss 3, p 730 (2024)
In the field of remote sensing technology, the semantic segmentation of remote sensing images carries substantial importance. The creation of high-quality models for this task calls for an extensive collection of image data. However, the manual annot
Externí odkaz:
https://doaj.org/article/3555fa2de2974827b2a6b5744b0dbefc
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 1, p 75 (2023)
A vessel automatic identification system (AIS) provides a large amount of dynamic vessel information over a large coverage area and data volume. The AIS data are a typical type of big geo-data with high dimensionality, large noise, heterogeneous dens
Externí odkaz:
https://doaj.org/article/c1734de34a414814852f907102cd23aa
Publikováno v:
Applied Sciences, Vol 13, Iss 7, p 4539 (2023)
Numerical methods, such as finite element or finite difference, have been widely used in the past decades for modeling solid mechanics problems by solving partial differential equations (PDEs). Differently from the traditional computational paradigm
Externí odkaz:
https://doaj.org/article/b5bcd84dc247424e8949424a71f48eab
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 5, Iss 2, p 13 (2016)
Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly devel
Externí odkaz:
https://doaj.org/article/5f7b689396554decbbd561200ac911cd
Publikováno v:
Memorias do Instituto Oswaldo Cruz, Vol 84, Pp 567-568 (1989)
An anthomyiid new genus Lopesohylemya with its type species L. qinghaiensis sp. n. from Qinghai, China, is described and figured. It is closely related to Eustalomyia histrio group, which is transferred to present new genus from Eustalomyia, it is su
Externí odkaz:
https://doaj.org/article/91c14d856a354a7990980235513df326
Publikováno v:
International Journal of Geographical Information Science. 33:1355-1376
Variation in the spatial heterogeneity of points reflects the evolutionary process or mechanism of geographical events. The key to depicting this variation is quantifying spatial heterogeneity. In ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::989b985a71350f7531ea726bb242e6f7
https://doi.org/10.1080/13658816.2019.1577432
https://doi.org/10.1080/13658816.2019.1577432
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 10, p 1793 (2024)
Underwater acoustic target recognition (UATR) is crucial for defense and ocean environment monitoring. Although traditional methods and deep learning approaches based on time–frequency domain features have achieved high recognition rates in certain
Externí odkaz:
https://doaj.org/article/6fbb870926ff43e195830b16eb5d8e25
Publikováno v:
International Journal of Geographical Information Science. 33:134-154
An origin-destination (OD) flow can be defined as the movement of objects between two locations. These movements must be determined for a range of purposes, and strong interactions can be visually ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9795dfad00b2564846dcd8cfb23eb7ad
https://doi.org/10.1080/13658816.2018.1516287
https://doi.org/10.1080/13658816.2018.1516287