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检索条件"机构=Key Laboratory of Technology in GeoSpatial Information Processing and Application System"
549 条 记 录,以下是381-390 订阅
排序:
3D Point Cloud Reconstruction of Vehicle using Inversely Mapping and Voting from CSAR Images
3D Point Cloud Reconstruction of Vehicle using Inversely Map...
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IEEE International Conference on Radar
作者: Shanshan Feng Yun Lin Fei Teng Wen Hong Key Laboratory of Technology in Geospatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences University of Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences Beijing China School of Electronic Information Engineering North China University of Technology Beijing China
3D reconstruction of object has raised much interest in the field of SAR. The feature of target at multi aspect angles can be obtained from sub-aperture images provided by circular SAR(CSAR), which is conducive to 3D ... 详细信息
来源: 评论
Model selection for high resolution InSAR coherence statistics over urban areas and its application in building detection
Model selection for high resolution InSAR coherence statisti...
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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)
作者: Yue Zhang Xian Sun Wenhui Diao Chenyuan Wang Guangluan Xu Hongqi Wang Institute of Electronic Chinese Academy of Sciences Beijing China Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China
The interferometric coherence map is derived from the cross-correlation of two registered synthetic aperture radar (SAR) images. It can give additional information complementary to the intensity image, or act as an in... 详细信息
来源: 评论
SALIENT SEED EXTRACTION BASED TARGET DETECTION IN SAR IMAGES
SALIENT SEED EXTRACTION BASED TARGET DETECTION IN SAR IMAGES
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IEEE International Geoscience and Remote Sensing Symposium
作者: Zongxu Pan Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
A salient seed extraction based target detection method is proposed in this paper, aiming to distinguish target points from background points in SAR images. Different from recent superpixel based method which generate... 详细信息
来源: 评论
Identity Regularized Sparse Representation for Automatic Target Recognition in Sar Images
Identity Regularized Sparse Representation for Automatic Tar...
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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)
作者: Zongxu Pan Lei Liu Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
An identity regularized sparse representation (IRSR) based SAR target recognition method is proposed in this paper. The method aims to find a transformation that can map the data to a transformed space, in which targe... 详细信息
来源: 评论
Spatiotemporal dynamics of coastal dead zones in the Gulf of Mexico over 20 years using remote sensing
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Science of the Total Environment 2025年 979卷
作者: Li, Yingjie Xia, Zilong Nguyen, Lan Wan, Ho Yi Wan, Luwen Wang, Mengqiu Jia, Nan Matli, Venkata Rohith Reddy Li, Yi Seeley, Megan Moran, Emilio F. Liu, Jianguo Center for Systems Integration and Sustainability Department of Fisheries and Wildlife Michigan State University East LansingMI48823 United States Environmental Science and Policy Program Michigan State University East LansingMI48823 United States Natural Capital Project Woods Institute for the Environment Doerr School of Sustainability Stanford University StanfordCA94305 United States Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Jiangsu Nanjing210023 China Department of Biological Sciences University of Calgary CalgaryABT2N 1N4 Canada Department of Wildlife California State Polytechnic University Humboldt ArcataCA95521 United States Department of Wildlife Ecology and Conservation University of Florida GainesvilleFL32611 United States Department of Earth System Science Stanford University StanfordCA94305 United States Earth and Environmental Sciences Michigan State University East LansingMI48824 United States School of Remote Sensing and Information Engineering Wuhan University Wuhan430072 China Department of Earth Sciences The University of Hong Kong Hong Kong 999077 China Center for Geospatial Analytics North Carolina State University RaleighNC27607 United States College of the Environment and Ecology Xiamen University Xiamen361102 China School of Geographical Sciences and Urban Planning Arizona State University TempeAZ85281 United States Center for Global Discovery and Conservation Science Arizona State University TempeAZ85281 United States Center for Global Change and Earth Observations Michigan State University East LansingMI48824 United States Department of Geography Environment and Spatial Science
Spreading marine dead zones (or hypoxia) are threatening coastal ecosystems and affecting billions of people's livelihoods globally. However, the lack of field observations makes it challenging to estimate dead zo... 详细信息
来源: 评论
Approach of SAR images simulations for target interpretations
Approach of SAR images simulations for target interpretation...
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IET International Radar Conference 2018, IRC 2018
作者: Zhang, Yueting Ding, Chibiao Lei, Bin Li, Fangfang Qiu, Xiaolan Institute of Electronics Chinese Academy of Sciences Beijing China Key Laboratory of Geo-spatial Information Processing and Application System Technology Chinese Academy of Sciences Zhongguancun Beiyitiao No. 9 Beijing China University of Chinese Academy of Sciences Yuquan Road No. 19 Beijing China
In this work, a novel approach for the simulation of synthetic aperture radar (SAR) images is proposed. Also, this approach aims to interpret the mechanisms of the dominated scattering centres in the SAR image. An att... 详细信息
来源: 评论
SAR Moving Target Segmentation and Removal Based on Deep Learning  8th
SAR Moving Target Segmentation and Removal Based on Deep L...
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8th EAI International Conference on Machine Learning and Intelligent Communications, MLICOM 2023
作者: Wu, Yifan Qi, Xiyu Huang, Lijia Zhang, Bingchen Yan, Lili Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China China Centre for Resources Satellite Data and Application Beijing100094 China
Synthetic Aperture Radar (SAR) stands as an integral part of advanced remote sensing technology. Nevertheless, practical applications experience inevitable disturbances from moving target noise, compromising both imag... 详细信息
来源: 评论
HIGH RESOLUTION SAR IMAGE CLASSIFICATION WITH DEEPER CONVOLUTIONAL NEURAL NETWORK
HIGH RESOLUTION SAR IMAGE CLASSIFICATION WITH DEEPER CONVOLU...
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IEEE International Geoscience and Remote Sensing Symposium
作者: Yue Zhang Xian Sun Hao Sun Zequn Zhang Wenhui Diao Kun Fu Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China Institute of Electronic Chinese Academy of Sciences Beijing China
Deeper architectures are proven to be beneficial for the classification performance obviously in computer vision field. Inspired by this, deep CNNs are expected to make progress in the SAR target classification proble... 详细信息
来源: 评论
Optimal sensor schedule under limited resources for two linear dynamical systems in wireless sensor network
Optimal sensor schedule under limited resources for two line...
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Asian Control Conference
作者: Jie Wang Jiahu Qin Qichao Ma Yu Kang Department of Automation University of Science and Technology of China Hefei China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing China
In this paper, we consider the problem of sensor scheduling under limited resources for two linear dynamical systems. We set up that only two sensor nodes were used to monitor the status of two systems, respectively, ... 详细信息
来源: 评论
Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attacks
arXiv
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arXiv 2024年
作者: Li, Ziqiang Zeng, Yueqi Xia, Pengfei Liu, Lei Fu, Zhangjie Li, Bin Nanjing University of Information Science and Technology China Big Data and Decision Lab University of Science and Technology of China China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System China
With the burgeoning advancements in the field of natural language processing (NLP), the demand for training data has increased significantly. To save costs, it has become common for users and businesses to outsource t... 详细信息
来源: 评论