机构

• 地理科学与资源研究所 [3]
• 自动化研究所 [3]
• 长春光学精密机械与物... [1]
• 遥感与数字地球研究所 [1]
• 合肥物质科学研究院 [1]

采集方式

• OAI收割 [9]

内容类型

• 期刊论文 [7]
• SCI/SSCI论文 [1]
• 会议论文 [1]

发表日期

• 2024 [1]
• 2022 [3]
• 2021 [1]
• 2019 [1]
• 2016 [1]
• 2014 [1]
• 更多

学科主题

• Geochemist... [1]

筛选

浏览/检索结果: 共9条，第1-9条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Automated Building Height Estimation Using Ice, Cloud, and Land Elevation Satellite 2 Light Detection and Ranging Data and Building Footprints 期刊论文  OAI收割 REMOTE SENSING, 2024, 卷号: 16, 期号: 2, 页码: 24 作者:  Cai, Panli;  Guo, Jingxian;  Li, Runkui;  Xiao, Zhen;  Fu, Haiyu   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/03/01 building height estimation  ICESat-2  LiDAR  building footprint  building photon selection   The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM2.5 from space 期刊论文  OAI收割 JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER, 2022, 卷号: 286 作者:  Li, Zhengqiang;  Hou, Weizhen;  Hong, Jin;  Fan, Cheng;  Wei, Yuanyuan   |  收藏  |  浏览/下载：39/0  |  提交时间：2022/12/23 Polarization crossfire suite  Fine particulate matter pm2  5 remote   sensing  Optimal estimation inversion  Aerosol layer height  Pcf   SCE-Net: Self- and Cross-Enhancement Network for Single-View Height Estimation and Semantic Segmentation 期刊论文  OAI收割 REMOTE SENSING, 2022, 卷号: 14, 期号: 9, 页码: 22 作者:  Xing, Siyuan;  Dong, Qiulei;  Hu, Zhanyi   |  收藏  |  浏览/下载：34/0  |  提交时间：2022/07/25 height estimation  semantic segmentation  single aerial image  convolutional neural networks  multi-task learning  deep metric learning   Gated Feature Aggregation for Height Estimation From Single Aerial Images 期刊论文  OAI收割 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 卷号: 19, 页码: 5 作者:  Xing, Siyuan;  Dong, Qiulei;  Hu, Zhanyi   |  收藏  |  浏览/下载：42/0  |  提交时间：2022/01/27 Estimation  Decoding  Logic gates  Training  Feature extraction  Testing  Encoding  Convolutional neural networks (CNNs)  gate mechanism  height estimation  progressive refinement   Single Tree Segmentation and Diameter at Breast Height Estimation With Mobile LiDAR 期刊论文  OAI收割 IEEE ACCESS, 2021, 卷号: 9, 页码: 24314-24325 作者:  Liu, Lulu;  Zhang, Aiwu   |  收藏  |  浏览/下载：36/0  |  提交时间：2021/04/25 Three-dimensional displays  Forestry  Vegetation  Laser radar  Estimation  Sensors  Measurement by laser beam  Diameter at breast height  mobile laser scanning  point cloud  single tree segmentation   Pedestrian Height Estimation and 3D Reconstruction Using Pixel-resolution Mapping Method Without Special Patterns 期刊论文  OAI收割 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 449-461 作者:  Bing-Xing Wu;  Suat Utku Ay;  Ahmed Abdel-Rahim   |  收藏  |  浏览/下载：22/0  |  提交时间：2021/02/22 Traffic monitoring application  spatial resolution  pixel-resolution mapping (P-RM) method  3D information  pedestrian height estimation.   High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite i 期刊论文  OAI收割 IEEE Transactions on Geoscience and Remote Sensing, 2016, 卷号: 54, 期号: 9, 页码: 5544-5552 作者:  Bao, Fangwen;  Gu, Xingfa;  Cheng, Tianhai;  Wang, Ying;  Guo, Hong 收藏  |  浏览/下载：46/0  |  提交时间：2017/04/24 POL-INSAR DATA  FOREST BIOMASS  PARAMETER-ESTIMATION  HEIGHT  RADAR   A Heuristic Approach to Reduce Atmospheric Effects in InSAR Data for the Derivation of Digital Terrain Models or for the Characterization of Forest Vertical Structure SCI/SSCI论文  OAI收割 2014 Ni W. J.; Sun G. Q.; Zhang Z. Y.; He Y. T.; Guo Z. F. 收藏  |  浏览/下载：32/0  |  提交时间：2014/12/24 Atmospheric effect  forest height  interferometric synthetic aperture  radar (InSAR)  interferometry  synthetic aperture radar (SAR)  sar interferometry  height estimation  radar  topography  band  uk   Adaptive deformation estimation of moving target by weight image analysis (EI CONFERENCE) 会议论文  OAI收割 2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, May 21, 2010 - May 24, 2010, Wuhan, China Bai X.-G.; Dai M. 收藏  |  浏览/下载：27/0  |  提交时间：2013/03/25 An algorithm based on weight image analysis is proposed for adaptive deformation estimation of moving target in mean-shift tracking method. At the first  we get the weight image from the target candidate region. Then  we analyze the differences between the object and background. According to that  the area estimation of the target can be converted into the image segmentation task. To realize the adaptive segmentation and estimation  we define the threshold as the maximum variance between object and background. Combining the estimated area and covariance matrix  we can estimate the width  height and orientation of the object. The experimental results on three representative video sequences validate its robustness to the deformable estimation of the targets. 2010 IEEE.