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SEMANTIC: 作品数：704被引量：970H指数：12; 导出分析报告; 相关领域：自动化与计算机技术更多>>; 相关作者：于戈王祥瑞陈明崔立真王海洋更多>>; 相关机构：清华大学华中师范大学上海交通大学北京航空航天大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家重点基础研究发展计划国家高技术研究发展计划国家社会科学基金更多>>

A novel semantic segmentation approach based on U-Net,WU-Net,and U-Net++deep learning for predicting areas sensitive to pluvial flood at tropical area: 《International Journal of Digital Earth》2023年第1期3661-3679,共19页Laura Melgar-García Francisco Martínez-álvarez Dieu Tien Bui Alicia Troncoso; The authors would like to thank the Spanish Ministry of Science and Innovation for the support under the projects PID2020-117954RB-C21 and TED2021-131311B-C22.; Floods remain one of the most devastating weather-induced disastersworldwide, resulting in numerous fatalities each year and severelyimpacting socio-economic development and the environment.Therefore, the ability to p...; 关键词：Flash-flood assessment convolutional networks climate change GIS

MDSNet:a multiscale decoupled supervision network for semantic segmentation of remote sensing images: 《International Journal of Digital Earth》2023年第1期2844-2861,共18页Jiangfan Feng Panyu Chen Zhujun Gu Maimai Zeng Wei Zheng; supported by the National Natural Science Foundation of China[grant number 41971365];the Major Science and Technology Project of the Ministry of Water Resources[grant number SKR-2022037];the Chongqing Graduate Research Innovation Project[grant number CYS22448].; Recent deep-learning successes have led to a new wave of semantic segmentation in remote sensing(RS)applications.However,most approaches rarely distinguish the role of the body and edge of RS ground objects;thus,our u...; 关键词：Semantic segmentation remote sensing images edge supervision multiscale

A labor-free index-guided semantic segmentation approach for urban vegetation mapping from high-resolution true color imagery: 《International Journal of Digital Earth》2023年第1期1640-1660,共21页Peng Zhang Cong Lin Shanchuan Guo Wei Zhang Hong Fang Peijun Du; supported by the National Key R&D Program of China under Grant 2022YFC3800802;the National Natural Science Foundation of China under Grant 42271472;the National Natural Science Foundation of China under Grant 42201338;the program A for Outstanding PhD candidate of Nanjing University under Grant 202201A010;the Research Project of Nanjing Research Institute of Surveying,Mapping and Geotechnical Investigation,Co.Ltd under Grant 2021RD02.; Accurate and timely information on urban vegetation(UV)can be used as an important indicator to estimate the health of cities.Due to the low cost of RGB cameras,true color imagery(TCI)has been widely used for high spa...; 关键词：Urban vegetation mapping Sustainable Development Goals(SDGs) cross-scale vegetation index(CSVI) semantic segmentation high-resolution true color imagery(TCI)

WMO:an ontology for the semantic enrichment of wetland monitoring data被引量：1: 《International Journal of Digital Earth》2023年第1期2189-2211,共23页Xin Xiao Hui Lin Chaoyang Fang; supported by National Natural Science Foundation of China[grant no U1811464];Graduate Inno-vation Fund Project of the Education Department of Jiangxi Province[grant no YC2022 B076]。; Rich observation data generated by ubiquitous sensors are vital for wetland monitoring,spanning from the prediction of natural disasters to emergency response.Such sensors use different data acquisition and descriptio...; 关键词：ONTOLOGY knowledge graph wetland monitoring semantic interoperability spatiotemporal data

A new method for the extraction of tailing ponds from very high-resolution remotely sensed images:PSVED: 《International Journal of Digital Earth》2023年第1期2681-2703,共23页Chengye Zhang Jianghe Xing Jun Li Shouhang Du Qiming Qin; supported by the National Key Research and Development Program[grant number:2022YFF1303301];The Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements[grant number:2022KFKTC001];The National Natural Science Foundation of China[grant number:42271480];The Fundamental Research Funds for the Central Universities[grant number:2023ZKPYDC10,BBJ2023026].; Automatic extraction of tailing ponds from Very High-Resolution(VHR)remotely sensed images is vital for mineral resource management.This study proposes a Pseudo-Siamese Visual Geometry Group Encoder-Decoder network(PS...; 关键词：Semantic segmentation tailing storage facilities Pseudo-Siamese network VHR images deep supervision mechanism

Towards POI-based large-scale land use modeling: spatial scale, semantic granularity, and geographic context: 《International Journal of Digital Earth》2023年第1期430-445,共16页Junchuan Fan Gautam Thakur; The combination of spatial distribution,semantic characteristics,and sometimes temporal dynamics of POIs inside a geographic region can capture its unique land use characteristics.Most previous studies on POI-based la...; 关键词：Land use POI geospatial semantic deep learning semantic granularity spatial scale

Automatic extraction and reconstruction of a 3D wireframe of an indoor scene from semantic point clouds: 《International Journal of Digital Earth》2023年第1期3239-3267,共29页Junyi Wei Hangbin Wu Han Yue Shoujun Jia Jintao Li Chun Liu; supported by the National Key Research and Development Program of China(Grant No.2021YFB2501103);the National Science Foundation of China(Grant No.42271429 and 42130106);the Key Research and Development Projects of Shanghai Science and Technology Commission(Grant No.21DZ1204103).; Accurate indoor 3D models are essential for building administration and applications in digital city construction and operation.Developing an automatic and accurate method to reconstruct an indoor model with semantics...; 关键词：Point cloud primitive extraction semantic optimization indoor model reconstruction

Semantic segmentation for remote sensing images based on an AD-HRNet model: 《International Journal of Digital Earth》2022年第1期2376-2399,共24页Xue Yang Xiang Fan Mingjun Peng Qingfeng Guan Luliang Tang; supported by the National Natural Science Foundation of China(No.42271449,41901394,41971405);open research fund program of Geomatics Technology and Application Key Laboratory of Qinghai Province.; Semantic segmentation for remote sensing images faces challenges of unbalanced category weight,rich context causing difficulties of recognition,blurred boundaries of multi-scale objects,and so on.To address these prob...; 关键词：Semantic segmentation convolutional neural networks dilated convolution attention mechanism remote sensing

Multi-class change detection of remote sensing images based on class rebalancing: 《International Journal of Digital Earth》2022年第1期1377-1394,共18页Huakang Tang Honglei Wang Xiaoping Zhang; supported by Guizhou Science and Technology Cooperation Program:[Grant Number QKH[2016]5103].; Multi-class change detection can make various ground monitoring projects more efficient and convenient.With the development of deep learning,the multi-class change detection methods have introduced Deep Neural Network...; 关键词：Multi-class change detection remote sensing class rebalancing semantic segmentation

Incorporating DeepLabv3+and object-based image analysis for semantic segmentation of very high resolution remote sensing images被引量：13: 《International Journal of Digital Earth》2021年第3期357-378,共22页Shouji Du Shihong Du Bo Liu Xiuyuan Zhang; was funded by the Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of Ministry of Natural Resources[grant number 2020-2-1];the National Natural Science Foundation of China[grant number 41871372].; Semantic segmentation of remote sensing images is an important but unsolved problem in the remote sensing society.Advanced image semantic segmentation models,such as DeepLabv3+,have achieved astonishing performance fo...; 关键词：Semantic segmentation DeepLabv3+ object-based image analysis DempsterShafer evidence theory conditional random field VHR images

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