Zobrazeno 1 - 10
of 84
pro vyhledávání: '"water segmentation"'
Publikováno v:
IEEE Access, Vol 12, Pp 52067-52085 (2024)
Accurate segmentation of river water in close-range Remote Sensing (RS) images is vital for efficient environmental monitoring and management. However, this task poses significant difficulties due to the dynamic nature of water, which exhibits varyin
Externí odkaz:
https://doaj.org/article/33d0f9bdb73d413994e8e91fefba0e17
Publikováno v:
Remote Sensing, Vol 16, Iss 4, p 720 (2024)
The frequent occurrence of global flood disasters leads to millions of people falling into poverty each year, which poses immense pressure on governments and hinders social development. Therefore, providing more data support for flood disaster detect
Externí odkaz:
https://doaj.org/article/950d4b91bfc94e33a25d74c1f4385ef3
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 119, Iss , Pp 103305- (2023)
To obtain reliable water segmentations from image data for real-time monitoring of river water levels, a comparison of 32 convolutional neural networks was performed. They were trained on a new river water segmentation dataset consisting of 1128 imag
Externí odkaz:
https://doaj.org/article/4cc473fbb3a44f81a87525c767d88a54
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 5, p 901 (2023)
Water segmentation is a critical task for ensuring the safety of unmanned surface vehicles (USVs). Most existing image-based water segmentation methods may be inaccurate due to light reflection on the water. The fusion-based method combines the paire
Externí odkaz:
https://doaj.org/article/f438705580f642a890b634184674560b
Publikováno v:
Computational Visual Media, Vol 6, Iss 1, Pp 65-78 (2020)
Abstract We develop a novel network to segment water with significant appearance variation in videos. Unlike existing state-of-the-art video segmentation approaches that use a pre-trained feature recognition network and several previous frames to gui
Externí odkaz:
https://doaj.org/article/8e01b3d7333241149d5ef8ef86831092
Autor:
LI Ning, NIU Shilin
Publikováno v:
Leida xuebao, Vol 9, Iss 1, Pp 174-184 (2020)
The extraction of water from Synthetic Aperture Radar (SAR) images is of great significance in water resources investigation and monitoring disasters. To deal with the problems of the insufficient accuracy of water boundaries extracted from middle-lo
Externí odkaz:
https://doaj.org/article/653b4671806f4ba3882cfb6a81c66bb5
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 103, Iss , Pp 102497- (2021)
The carrying capacity of water resources is key to the sustainable development of arid and semi-arid regions. There are important challenges related to the detection of discontinuous and crooked water bodies in the vast Mongolian Plateau, despite the
Externí odkaz:
https://doaj.org/article/079d6693c6ac44e1b4e4896261f81fbe
Publikováno v:
Remote Sensing, Vol 14, Iss 22, p 5753 (2022)
Distinguishing sea ice and water is crucial for safe navigation and carrying out offshore activities in ice zones. However, due to the complexity and dynamics of the ice–water boundary, it is difficult for many deep learning-based segmentation algo
Externí odkaz:
https://doaj.org/article/877aefe871894bab96d3ceff8cd71b14
Publikováno v:
Leida xuebao, Vol 8, Iss 3, Pp 400-412 (2019)
Water segmentation of real SAR images is of great significance in military and civilian applications such as ship target detection and disaster monitoring. To solve the issues of poor robustness and inaccurate segmentation of traditional water segmen
Externí odkaz:
https://doaj.org/article/cc34422e296b4868ba3585b94dd617c1
Publikováno v:
IEEE Access, Vol 7, Pp 95430-95442 (2019)
The use of synthetic aperture radar (SAR) images for water segmentation can accurately extract the boundaries of water areas and is of great significance for studying the temporal and spatial changes of lakes and other environmental elements. In view
Externí odkaz:
https://doaj.org/article/31dfb26500284f30825f572a4f7572da