Zobrazeno 1 - 10
of 205
pro vyhledávání: '"remote sensing image segmentation"'
Publikováno v:
Frontiers in Environmental Science, Vol 12 (2024)
Jiajin Mountain, where the giant pandas reside, is an essential nature reserve in China. To comprehend the land use classification of the habitat, this article proposes a remote sensing interpretation algorithm based on spatial case reasoning, known
Externí odkaz:
https://doaj.org/article/73017ffb5eff4b05a6f0332db7ce79d2
Publikováno v:
Remote Sensing, Vol 16, Iss 11, p 1889 (2024)
Construction waste is an inevitable byproduct of urban renewal, causing severe pressure on the environment, health, and ecology. Accurately estimating the production of construction waste is crucial for assessing the consumption of urban renewal. How
Externí odkaz:
https://doaj.org/article/97aee7e3d1ef4b18ac76cf4d025d823c
Autor:
Xiuxia Li
Publikováno v:
AIMS Geosciences, Vol 8, Iss 4, Pp 658-668 (2022)
People's diversified tourism needs provide a broad development space and atmosphere for various tourism forms. The geographic resource information of the tourism unit can vividly highlight the unit's geographic spatial location and reflect the indivi
Externí odkaz:
https://doaj.org/article/29b93900dcfe4de49c81e8a29e0b8e54
Akademický článek
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Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 3, Iss 1, Pp 52-63 (2020)
It is proposed a high resolution remote sensing image segmentation method which combines static minimum spanning tree (MST) tessellation considering shape information and the RHMRF-FCM algorithm. It solves the problems in the traditional pixel-based
Externí odkaz:
https://doaj.org/article/ddea775a2ba740319d03f94464f70750
Publikováno v:
Remote Sensing, Vol 15, Iss 4, p 1001 (2023)
The accurate classification of forest types is critical for sustainable forest management. In this study, a novel multiscale global graph convolutional neural network (MSG-GCN) was compared with random forest (RF), U-Net, and U-Net++ models in terms
Externí odkaz:
https://doaj.org/article/5b963fc0b0e745ab90e344979ec01c90
Publikováno v:
Applied Sciences, Vol 13, Iss 4, p 2261 (2023)
Transformer models have achieved great results in the field of computer vision over the past 2 years, drawing attention from within the field of remote sensing. However, there are still relatively few studies on this model in the field of remote sens
Externí odkaz:
https://doaj.org/article/871a279fc4d54c858f206efeac2c01b3
Publikováno v:
Remote Sensing, Vol 15, Iss 1, p 108 (2022)
The performance of deep neural networks depends on the accuracy of labeled samples, as they usually contain label noise. This study examines the semantic segmentation of remote sensing images that include label noise and proposes an anti-label-noise
Externí odkaz:
https://doaj.org/article/92ed07e053ac427382c2d9ed94801549
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 4875 (2022)
Affected by solar radiation, atmospheric windows, radiation aberrations, and other air and sky environmental factors, remote sensing images usually contain a large amount of noise and suffer from problems such as non-uniform image feature density. Th
Externí odkaz:
https://doaj.org/article/741557442ccb48e7a75ccf650dbe50c8
Akademický článek
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