Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Anzhu Yu"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104014- (2024)
Deep-learning based approaches have been proven effective for Digital Elevation Model (DEM) super-resolution (SR) tasks. Previous networks typically treat DEM elevation values as single-channel image for input. However, DEM images alone cannot fully
Externí odkaz:
https://doaj.org/article/85480da703164a43ab7a9b15934cf98c
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104189- (2024)
Stereo matching is essential for establishing pixel-level correspondences and estimating depth in scene reconstruction. However, applying stereo matching networks to UAV scenarios presents unique challenges due to varying altitudes, angles, and rapid
Externí odkaz:
https://doaj.org/article/c131c2d65861457d96167cba152398ab
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104164- (2024)
Automatic 3D reconstruction from spaceborne charge-coupled device (CCD) optical imagery is still a challenge as the rational functional model (RFM) based reconstruction pipeline failed to amount to the advances of pinhole based approaches in computer
Externí odkaz:
https://doaj.org/article/6618e0bae01a49e0974e29b14de2b9f8
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16577-16591 (2024)
Building extraction is a challenging task in remote sensing images (RSI) interpretation. Fusing RSI from different sources, such as high-resolution RSI and LiDAR, is a common strategy to improve the building extraction accuracy. However, the acquisit
Externí odkaz:
https://doaj.org/article/c442f302645643bebf75c85a63b6bba0
Publikováno v:
European Journal of Remote Sensing, Vol 56, Iss 1 (2023)
ABSTRACTIn recent years, deep learning methods have been widely used for the classification of hyperspectral images. However, their limited availability under the condition of small samples remains a serious issue. Moreover, the current mainstream ap
Externí odkaz:
https://doaj.org/article/cce4688d4f8e4b67beec159920ca9f17
Publikováno v:
European Journal of Remote Sensing, Vol 56, Iss 1 (2023)
ABSTRACTDeep learning instantiated by convolutional neural networks has achieved great success in high-resolution remote-sensing image change detection. However, such networks have a limited receptive field, being unable to extract long-range depende
Externí odkaz:
https://doaj.org/article/0593218fc38548b5b16f937417683ed7
Publikováno v:
Remote Sensing, Vol 16, Iss 5, p 842 (2024)
Deep learning, which is a dominating technique in artificial intelligence, has completely changed image understanding over the past decade. As a consequence, the sea ice extraction (SIE) problem has reached a new era. We present a comprehensive revie
Externí odkaz:
https://doaj.org/article/89e0b2fadb26494588c821397c26b169
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 2942-2953 (2023)
Stereo matching is a fundamental task in 3-D scene reconstruction. Recently, deep learning-based methods have proven effective on some benchmark datasets, such as KITTI and SceneFlow. Unmanned aerial vehicles (UAVs) are commonly used for surface obse
Externí odkaz:
https://doaj.org/article/ef0db842c3234ac3bd09a30c27532743
Publikováno v:
European Journal of Remote Sensing, Vol 55, Iss 1, Pp 103-114 (2022)
In recent years, the wide use of deep learning based methods has greatly improved the classification performance of hyperspectral image (HSI). As an effective method to improve the performance of deep convolution networks, attention mechanism is also
Externí odkaz:
https://doaj.org/article/4a73b3769f4946338d5aaebf0a160ae3
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 120, Iss , Pp 103346- (2023)
Building change detection (CD) using remote sensing images plays a vital role in urban development, and deep learning models attracted attention for their potential to accomplish CD tasks automatically. However, most methods are still facing challeng
Externí odkaz:
https://doaj.org/article/ff4d0de5440e4865a5bfacb49ffe64dd