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检索条件"机构=Key Laboratory of Technology in Geo-Spatial information Processing and Application System"
588 条 记 录,以下是311-320 订阅
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
A TOPSAR Calibration Method for processing system of GF3 Next Generation  6
A TOPSAR Calibration Method for Processing System of GF3 Nex...
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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019
作者: Yin, Di Han, Bing Sun, Jili Chen, Aiping Zhao, Liangbo Yuan, Xinzhe Zhong, Lihua Hu, Yuxin University of Chinese Academy of Sciences Beijing100049 China Institute of Electronics Chinese Academy of Sciences Beijing100190 China Beijing Institute of Telemetry and Telecommunications Technology Beijing100094 China Chinese Academy of Space Technology Beijing100094 China National Satellite Ocean Application Service State Oceanic Administration Beijing100081 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences Beijing100190 China
TOPSAR is an earth-imaging technique, which can provide wide swath coverage. The paper introduces a TOPSAR focusing and calibrating experiment based on the TOPSAR data acquired by Gaofen3(GF3). In this paper, we first... 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
Recent Widespread Deceleration of Global Surface Urban Heat Islands Unveiled by Satellites
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geophysical Research Letters 2025年 第12期52卷
作者: Wenfeng Zhan Long Li T. C. Chakraborty Leiqiu Hu Dazhong Wang Weilin Liao Shasha Wang Huilin Du Fan Huang Chunli Wang Zihan Liu Manchun Li Jiangsu Provincial Key Laboratory for Advanced Remote Sensing and Geographic Information Technology International Institute for Earth System Science Nanjing University Nanjing China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing China Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing China Pacific Northwest National Laboratory Richland WA USA Department of Atmospheric Science University of Alabama in Huntsville Huntsville AL USA Guangdong Key Laboratory for Urbanization and Geo-Simulation School of Geography and Planning Sun Yat-sen University Guangzhou China School of Geography and Ocean Science Nanjing University Nanjing China
Tracking the temporal dynamics of urban heat island (UHI) is critical for urban heat adaptation and mitigation strategies. However, whether UHI trends have shifted recently and their underlying drivers remain unknown.... 详细信息
来源: 评论
Warning of Rainfall-Induced Landslide in Bazhou District
Warning of Rainfall-Induced Landslide in Bazhou District
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IEEE International Symposium on geoscience and Remote Sensing (IGARSS)
作者: Mujie Li Mingcang Zhu Yang Hec Zhanyong He Na Wang Zezhong Zheng Guoqing Zhou School of Resources and Environment University of Electronic Science and Technology of China Chengdu Sichuan PRC Chengdu Sichuan PRC Sichuan Research Institute for Eco-system Restoration & Geo-disaster Prevention Chengdu Sichuan PRC Guangxi Key Laboratory for Spatial Information and Geomatics Guilin University of Technology Guilin Guangxi PRC
Landslide disasters have caused incalculable losses to human. In China, 90% occurrence of landslides are directly induced by rainfall or indirectly related to rainfall. Because of its geographical location and the cli... 详细信息
来源: 评论
Parameter prediction method of SAR target simulation based on convolutional neural networks  12
Parameter prediction method of SAR target simulation based o...
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12th European Conference on Synthetic Aperture Radar, EUSAR 2018
作者: Shengren, Niu Xiaolan, Qiu Lingxiao, Peng Bin, Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute ofElectronics Chinese Academy of Sciences University of Chinese Academy of Sciences China Suzhou Institute Institute of Electronics Chinese Academy of Sciences China
SAR image simulation plays a useful role in SAR target interpretation and recognition. The current SAR target simulation methods require high precision of models and simulation parameters, and are only forward process... 详细信息
来源: 评论
Bell State Preparation Based on Switching Between Quantum system Models
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Journal of systems Science & Complexity 2017年 第2期30卷 347-356页
作者: ZHOU Juan KUANG Sen CONG Shuang Department of Automation University of Science and Technology of ChinaHefei 230027China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science
For the preparation of any target Bell state under continuous quantum measurement, this paper proposes a method which achieves the control objective by switching between two different models or by switching between tw... 详细信息
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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
Self-Tuning Asynchronous Filter for Linear Gaussian system and applications
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IEEE/CAA Journal of Automatica Sinica 2018年 第6期5卷 1054-1061页
作者: Wenjun Lv Yu Kang Yunbo Zhao Department of Automation University of Science and Technology of ChinaHefei 230027China State Key Laboratory of Fire Science Department of Automation and Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei 230027China Key Laboratory of Technology in GeoSpatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China
In this paper, optimal filtering problem for a class of linear Gaussian systems is studied. The system states are updated at a fast uniform sampling rate and the measurements are sampled at a slow uniform sampling rat... 详细信息
来源: 评论
Predictive auto-encoding network for blind stereoscopic image quality assessment
arXiv
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arXiv 2019年
作者: Xu, Jiahua Zhou, Wei Chen, Zhibo Ling, Suiyi Le Callet, Patrick CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China quipe Image Perception et Interaction Laboratoire des Sciences du Numrique de Nantes Universit de Nantes Nantes44300 France
Stereoscopic image quality assessment (SIQA) has encountered non-trivial challenges due to the fast proliferation of 3D contents. In the past years, deep learning oriented SIQA methods have emerged and achieved specta... 详细信息
来源: 评论