Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Changmiao Hu"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10468-10489 (2024)
Remote sensing images are usually contaminated by opaque cloud and shadow regions when acquired, and thus cloud and shadow detections become one of the essential prerequisites for the restoration of the objects of interest before further processing a
Externí odkaz:
https://doaj.org/article/c8cbb8cdb1eb4f5385f53c011b65029f
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 2, Pp 4687-4706 (2023)
ABSTRACTRemote sensing technology has been widely used for marine monitoring. However, due to the limitations of sensor technologies and data sources, effective monitoring of marine ships at night remains challenging. To address these challenges, our
Externí odkaz:
https://doaj.org/article/c11d6794adda4015bb7bdef1e264260f
Publikováno v:
Applied Sciences, Vol 14, Iss 9, p 3568 (2024)
Cementing is a critical link in oil and gas exploitation, in which slurry density control is particularly important. In this study, we examined a slurry mixing control system in order to solve the problem of time delays in the mixing system. The mode
Externí odkaz:
https://doaj.org/article/cf60727c017346e1980adaadecfb9881
Publikováno v:
Remote Sensing, Vol 15, Iss 21, p 5229 (2023)
We have developed an algorithm for cloud detection in Chinese GF-1/6 satellite multispectral images, allowing us to generate cloud masks at the pixel level. Due to the lack of shortwave infrared and thermal infrared bands in the Chinese GF-1/6 satell
Externí odkaz:
https://doaj.org/article/9ea8be85d1594ae982baea8423dcd98b
Publikováno v:
Remote Sensing, Vol 15, Iss 7, p 1955 (2023)
The Landsat and Sentinel series satellites contain their own quality tagging data products, marking the source image pixel by pixel with several specific semantic categories. These data products generally contain categories such as cloud, cloud shado
Externí odkaz:
https://doaj.org/article/853145570ce44233b11e00a4dc9ef16a
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3052-3069 (2021)
Haze removal is still an essential prerequisite for image processing and computer vision tasks, and joint inference and refinement of transmission maps remain challenging in the physical scattering model-based haze removal methods. In this article, w
Externí odkaz:
https://doaj.org/article/8765eb41ac7f4cb9a20403465b25c455
Publikováno v:
IEEE Access, Vol 8, Pp 46151-46161 (2020)
Cloud and cloud shadow are common issues in optical satellite imagery, which greatly reduce the usage of data archive. As for the Landsat data, great advances have been made on detecting cloud and cloud shadow. However, few studies were performed on
Externí odkaz:
https://doaj.org/article/729459177d4244d5ac817f95140e0383
Publikováno v:
Remote Sensing, Vol 15, Iss 5, p 1382 (2023)
Built-up areas and buildings are two main targets in remote sensing research; consequently, automatic extraction of built-up areas and buildings has attracted extensive attention. This task is usually difficult because of boundary blur, object occlus
Externí odkaz:
https://doaj.org/article/3b480e8cfac449c7a31db26df0e489c0
Publikováno v:
Remote Sensing, Vol 14, Iss 12, p 2778 (2022)
Satellite Image Time Series (SITS) record the continuous temporal behavior of land cover types and thus provide a new perspective for finer-grained land cover classification compared with the usual spectral and spatial information contained in a stat
Externí odkaz:
https://doaj.org/article/b6b7de70acaf49a7a3dd26f017fed81c
Refined UNet V4: End-to-End Patch-Wise Network for Cloud and Shadow Segmentation with Bilateral Grid
Publikováno v:
Remote Sensing, Vol 14, Iss 2, p 358 (2022)
Remote sensing images are usually contaminated by cloud and corresponding shadow regions, making cloud and shadow detection one of the essential prerequisites for processing and translation of remote sensing images. Edge-precise cloud and shadow segm
Externí odkaz:
https://doaj.org/article/f3e2e37373a244159da40eb7d559f5da