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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301-310 订阅
排序:
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
An Energy Efficient Carry-Free Inner Product Unit
An Energy Efficient Carry-Free Inner Product Unit
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Signal, information and Data processing (ICSIDP), IEEE International Conference on
作者: Wen Yan Miloš D. Ercegovac Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China University of California Los Angeles CA USA
An energy efficient truncated inner product unit is proposed in this paper. The proposed unit is pipelined and processes the m pairs of n-bit operands in serial, so that only one unit is required and it can be reused ...
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Waterline mapping of inland great lake with subpixel accuracy from GF-3 SAR images  6
Waterline mapping of inland great lake with subpixel accurac...
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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019
作者: Li, Ning Niu, Shilin Wang, Robert Wu, Lin Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China Department of Space Microwave Remote Sensing System Institute of Electronics Chinese Academy of Sciences Beijing100190 China
High-accuracy waterline mapping with Synthetic Aperture Radar (SAR) images is a challenging task because of the inhomogeneities of SAR imagery caused by the speckle noise and complex terrain. This paper presents a nov... 详细信息
来源: 评论
A sub-pixel level map projection conversion method for high resolution of GF3 satellite products  12
A sub-pixel level map projection conversion method for high ...
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12th European Conference on Synthetic Aperture Radar, EUSAR 2018
作者: Wang, Wentao Liu, Jiayin Huang, Lijia Key Laboratory of Technology on Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China
The GF-3 satellite launched in August 2016, is a C-band synthetic aperture radar(SAR) in China. With a resolution up to 1 m, GF-3 SAR imagery have made feasible the generation large-scale high resolution maps which ne... 详细信息
来源: 评论
Progressive unsupervised person re-identification by tracklet association with spatio-temporal regularization
arXiv
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arXiv 2019年
作者: Xie, Qiaokang Zhou, Wengang Qi, Guo-Jun Tian, Qi Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei230027 China Huawei Cloud EI Product Department Huawei Noah's Ark Laboratory
Existing methods for person re-identification (Re-ID) are mostly based on supervised learning which requires numerous manually labeled samples across all camera views for training. Such a paradigm suffers the scalabil... 详细信息
来源: 评论
Transform-Invariant Convolutional Neural Networks for Image Classification and Search
arXiv
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arXiv 2019年
作者: Shen, Xu Tian, Xinmei He, Anfeng Sun, Shaoyan Tao, Dacheng CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia
Convolutional neural networks (CNNs) have achieved state-of-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invariant to spatial transformations of imag... 详细信息
来源: 评论
Patch reordering: A novel way to achieve rotation and translation invariance in convolutional neural networks
arXiv
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arXiv 2019年
作者: Shen, Xu Tian, Xinmei Sun, Shaoyan Tao, Dacheng CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China Centre for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia
Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance on many visual recognition tasks. However, the combination of convolution and pooling operations only shows invariance to small local... 详细信息
来源: 评论
Author Correction: Mapping annual 10-m soybean cropland with spatiotemporal sample migration
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Scientific data 2024年 第1期11卷 565页
作者: Hongchi Zhang Zihang Lou Dailiang Peng Bing Zhang Wang Luo Jianxi Huang Xiaoyang Zhang Le Yu Fumin Wang Linsheng Huang Guohua Liu Shuang Gao Jinkang Hu Songlin Yang Enhui Cheng Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. University of Chinese Academy of Sciences Beijing 100094 China. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. pengdl@***. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. pengdl@***. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. University of Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. Jiangxi Nuclearindustry Surveying and Mapping Institute Group Co. Ltd Nanchang 330038 China. College of Land Science and Technology China Agricultural University Beijing 100083 China. Geospatial Sciences Center of Excellence Department of Geography Geospatial Sciences South Dakota State University Brookings SD 57007 USA. Department of Earth System Science Tsinghua University Beijing 100084 China. Institute of Applied Remote Sensing & Information Technology Zhejiang University Hangzhou 310058 China. National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei 230601 China. Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai 200120 China.
来源: 评论
Sampled-data Observer Design for a Class of Stochastic Nonlinear systems Based on the Approximate Discrete-time Models
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IEEE/CAA Journal of Automatica Sinica 2017年 第3期4卷 507-511页
作者: Xinxin Fu Yu Kang Pengfei Li Department of Automation University of Science and Technology of China State Key Laboratory of Fire Science Department of AutomationInstitute of Advanced TechnologyUniversity of Science and Technology of China Key Laboratory of Technology in GeoSpatial Information Processing and Application System Chinese Academy of Sciences IEEE
In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear ***-Maruyama approximation was investigated in this paper because it is the basis of other higher precision nume... 详细信息
来源: 评论
Real-time correlation tracking via joint model compression and transfer
arXiv
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arXiv 2019年
作者: Wang, Ning Zhou, Wengang Song, Yibing Ma, Chao Li, Houqiang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China Tencent AI Lab Shenzhen China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China
Correlation filters (CF) have received considerable attention in visual tracking because of their computational efficiency. Leveraging deep features via off-the-shelf CNN models (e.g., VGG), CF trackers achieve state-... 详细信息
来源: 评论