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科研机构
植物研究所 [8]
理论物理研究所 [3]
烟台海岸带研究所 [1]
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期刊论文 [12]
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2022 [1]
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2019 [4]
2018 [4]
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Imaging S... [12]
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学科主题:Imaging Science & Photographic Technology
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Loess Landslide Detection Using Object Detection Algorithms in Northwest China
期刊论文
REMOTE SENSING, 2022, 卷号: 14, 期号: 5
作者:
Ju, Yuanzhen
;
Xu, Qiang
;
Jin, Shichao
;
Li, Weile
;
Su, Yanjun
收藏
  |  
浏览/下载:0/0
  |  
提交时间:2024/03/07
loess landslide
google earth image
deep learning
automatic identification
object detection
A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 卷号: 13, 页码: 3958-3974
作者:
Jin, Shichao
;
Sun, Yanjun
;
Zhao, Xiaoqian
;
Hu, Tianyu
;
Guo, Qinghua
收藏
  |  
浏览/下载:83/0
  |  
提交时间:2022/03/01
Digital terrain model (DTM)
deep learning
fully convolutional neural network (FCN)
ground filtering
light detection and ranging (LiDAR)
Dynamic Synthetic Minority Over-Sampling Technique-Based Rotation Forest for the Classification of Imbalanced Hyperspectral Data
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 卷号: 12, 期号: 7, 页码: 2159-2169
作者:
Feng, Wei
;
Dauphin, Gabriel
;
Huang, Wenjiang
;
Quan, Yinghui
;
Bao, Wenxing
收藏
  |  
浏览/下载:0/0
  |  
提交时间:2020/06/16
ENSEMBLES
SELECTION
SMOTE
Dynamic Synthetic Minority Over-Sampling Technique-Based Rotation Forest for the Classification of Imbalanced Hyperspectral Data
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 卷号: 12, 期号: 7, 页码: 2159-2169
作者:
Feng, Wei
;
Dauphin, Gabriel
;
Huang, Wenjiang
;
Quan, Yinghui
;
Bao, Wenxing
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2020/11/26
ENSEMBLES
SELECTION
SMOTE
Dynamic Synthetic Minority Over-Sampling Technique-Based Rotation Forest for the Classification of Imbalanced Hyperspectral Data
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 卷号: 12, 期号: 7, 页码: 2159-2169
作者:
Feng, Wei
;
Dauphin, Gabriel
;
Huang, Wenjiang
;
Quan, Yinghui
;
Bao, Wenxing
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2020/11/26
ENSEMBLES
SELECTION
SMOTE
An Object-Based Strategy for Improving the Accuracy of Spatiotemporal Satellite Imagery Fusion for Vegetation-Mapping Applications
期刊论文
REMOTE SENSING, 2019, 卷号: 11, 期号: 24
作者:
Guan, Hongcan
;
Su, Yanjun
;
Hu, Tianyu
;
Chen, Jin
;
Guo, Qinghua
收藏
  |  
浏览/下载:24/0
  |  
提交时间:2022/01/06
spatiotemporal data fusion
object-based framework
similar pixel
vegetation mapping
Evaluating the Performance of Sentinel-2, Landsat 8 and Pleiades-1 in Mapping Mangrove Extent and Species
期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 9
作者:
Wang, Dezhi
;
Wan, Bo
;
Qiu, Penghua
;
Su, Yanjun
;
Guo, Qinghua
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2022/02/25
mangroves
species
Sentinel-2
Landsat 8
Pleiades-1
random forest
Artificial Mangrove Species Mapping Using Pleiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms
期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 2
作者:
Wang, Dezhi
;
Wan, Bo
;
Qiu, Penghua
;
Su, Yanjun
;
Guo, Qinghua
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2022/02/25
artificial mangrove
object-based
pixel-based
decision tree
random forest
support vector machine
Land use and land cover change in Inner Mongolia - understanding the effects of China's re-vegetation programs
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2018, 卷号: 204, 页码: 918-930
作者:
Yin, He
;
Pflugmacher, Dirk
;
Li, Ang
;
Li, Zhengguo
;
Hostert, Patrick
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2022/02/25
Land use and land cover change
Deforestation
Afforestation
Cropland retirement
MODIS time series
Trajectory-based approach
Inner Mongolia
Machine learning
Random forest
Probability scores
An Ensemble of Classifiers Based on Positive and Unlabeled Data in One-Class Remote Sensing Classification
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 卷号: 11, 期号: 2, 页码: 572-584
作者:
Liu, Ran
;
Li, Wenkai
;
Liu, Xiaoping
;
Lu, Xingcheng
;
Li, Tianhong
收藏
  |  
浏览/下载:42/0
  |  
提交时间:2022/02/25
Classifier ensemble
one-class classification
positive and unlabeled learning (PUL)
weighted average
weighted vote
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