Zobrazeno 1 - 10
of 91
pro vyhledávání: '"global context information"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12138-12152 (2024)
Water body extraction is an essential mission in the field of semantic segmentation of remote sensing images. It plays a significant role in natural disaster prevention, water resources utilization, hydrological monitoring, and other territories. In
Externí odkaz:
https://doaj.org/article/685846f7eb174f3e817357dbdc24d737
Publikováno v:
Remote Sensing, Vol 16, Iss 20, p 3774 (2024)
Generating pixel-level annotations for semantic segmentation tasks of high-resolution remote sensing images is both time-consuming and labor-intensive, which has led to increased interest in unsupervised methods. Therefore, in this paper, we propose
Externí odkaz:
https://doaj.org/article/271946437dad4a5bbb798e51e530d161
Akademický článek
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Publikováno v:
Tehnički Vjesnik, Vol 29, Iss 5, Pp 1567-1575 (2022)
As an important research direction in the field of pattern recognition, semantic segmentation has become an important method for remote sensing image information extraction. However, due to the loss of global context information, the effect of semant
Externí odkaz:
https://doaj.org/article/8beeda63f607413fa41a9f2e2b706ef2
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 1150-1162 (2022)
Deep convolutional neural networks have become an indispensable method in remote sensing image scene classification because of their powerful feature extraction capabilities. However, the ability of the models to extract multiscale features and globa
Externí odkaz:
https://doaj.org/article/bec92b7db0fb426080b08072628066dc
Akademický článek
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Akademický článek
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Publikováno v:
Remote Sensing, Vol 15, Iss 19, p 4649 (2023)
Semantic segmentation of high-resolution remote sensing images holds paramount importance in the field of remote sensing. To better excavate and fully fuse the features in high-resolution remote sensing images, this paper introduces a novel Global an
Externí odkaz:
https://doaj.org/article/44c3c35372b64a44b401c7801da305ed
Publikováno v:
IEEE Access, Vol 9, Pp 134649-134659 (2021)
The low resolution and less feature information of small targets make it difficult to recognize and locate, which greatly hinders the improvement of object detection accuracy. In this paper, an object detection model (TDFP) based on CNN and transform
Externí odkaz:
https://doaj.org/article/7a3949bbfa86479c952f56dbc4f85169
Publikováno v:
GIScience & Remote Sensing, Vol 56, Iss 5, Pp 749-768 (2019)
Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground obj
Externí odkaz:
https://doaj.org/article/b8d15124673d4328ac663e21f810a356