×
验证码:
换一张
忘记密码?
记住我
CORC
首页
科研机构
检索
知识图谱
申请加入
托管服务
登录
注册
在结果中检索
科研机构
地理科学与资源研究... [23]
暨南大学 [4]
山东大学 [3]
中国农业科学院 [2]
吉林大学白求恩第一医... [1]
复旦大学上海医学院 [1]
更多...
内容类型
期刊论文 [29]
EI期刊论文 [4]
专利 [1]
发表日期
2021 [3]
2020 [5]
2019 [2]
2018 [6]
2017 [2]
2015 [1]
更多...
学科主题
Civil; Env... [1]
Engineerin... [1]
Environmen... [1]
Geoscience... [1]
Materials ... [1]
Multidisci... [1]
更多...
×
知识图谱
CORC
开始提交
已提交作品
待认领作品
已认领作品
未提交全文
收藏管理
QQ客服
官方微博
反馈留言
浏览/检索结果:
共34条,第1-10条
帮助
已选(
0
)
清除
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
作者升序
作者降序
题名升序
题名降序
发表日期升序
发表日期降序
提交时间升序
提交时间降序
Geospatial constrained optimization to simulate and predict spatiotemporal trends of air pollutants
期刊论文
SPATIAL STATISTICS, 2021, 卷号: 45, 页码: 28
作者:
Li, Lianfa
收藏
  |  
浏览/下载:40/0
  |  
提交时间:2021/11/05
Constrained optimization
Domain knowledge
Spatiotemporal patterns
Air pollutant
Prediction
Uncertainty
Encoder-Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 9, 页码: 4217-4230
作者:
Li, Lianfa
;
Fang, Ying
;
Wu, Jun
;
Wang, Jinfeng
;
Ge, Yong
收藏
  |  
浏览/下载:80/0
  |  
提交时间:2021/11/05
Bias
deep learning
encoder-decoder
full residual deep network
non-linear regression
prediction of satellite aerosol optical depth (AOD) and PM2.5
spatiotemporal modeling
Spatiotemporal estimation of satellite-borne and ground-level NO2 using full residual deep networks
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2021, 卷号: 254, 页码: 22
作者:
Li, Lianfa
;
Wu, Jiajie
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2021/03/15
OMI-NO2 columns
Imputation of missing values
Full residual deep network
Bagging
Ground-level NO2 estimation
Traffic and land-use variables
Uncertainty
Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke
期刊论文
ENVIRONMENT INTERNATIONAL, 2020, 卷号: 145, 页码: 16
作者:
Li, Lianfa
;
Girguis, Mariam
;
Lurmann, Frederick
;
Pavlovic, Nathan
;
McClure, Crystal
收藏
  |  
浏览/下载:122/0
  |  
提交时间:2021/03/16
PM2.5
Machine learning
Air pollution exposure
Wildfires
Remote sensing
California
High spatiotemporal resolution
Multi-Scale Residual Deep Network for Semantic Segmentation of Buildings with Regularizer of Shape Representation
期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 18, 页码: 21
作者:
Wang, Chengyi
;
Li, Lianfa
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2021/03/16
multiple scales
residual deep ensemble learning
regularizer
shape representation
semantic segmentation of buildings
Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation
期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 3, 页码: 20
作者:
Li, Lianfa
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2020/05/19
parameter inversion
aerosol optical depth
PBLH
ground-based AOD
PM2
5
automatic differentiation
Spatiotemporal imputation of MAIAC AOD using deep learning with downscaling
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2020, 卷号: 237, 页码: 17
作者:
Li, Lianfa
;
Franklin, Meredith
;
Girguis, Mariam
;
Lurmann, Frederick
;
Wu, Jun
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2020/05/19
Aerosol Optical Depth
MAIAC
MERRA-2 GMI Replay Simulation
Deep learning
Downscaling
Missingness imputation
Air quality
A Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5
期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 2, 页码: 27
作者:
Li, Lianfa
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2020/05/19
PM2.5
satellite AOD
deep learning
autoencoder
residual network
exposure estimation
high spatiotemporal resolution
Deep Residual Autoencoder with Multiscaling for Semantic Segmentation of Land-Use Images
期刊论文
REMOTE SENSING, 2019, 卷号: 11, 期号: 18, 页码: 24
作者:
Li, Lianfa
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2020/05/19
residual learning
autoencoder
multiscale
atrous spatial pyramid pooling
semantic segmentation
remotely sensed land-use images
Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions
期刊论文
ENVIRONMENT INTERNATIONAL, 2019, 卷号: 128, 页码: 310-323
作者:
Li, Lianfa
;
Girguis, Mariam
;
Lurmann, Frederick
;
Wu, Jun
;
Urman, Robert
收藏
  |  
浏览/下载:53/0
  |  
提交时间:2019/09/24
Air pollution
Nitrogen oxides
Spatiotemporal variability
Generalization
Machine learning
Cluster methods
©版权所有 ©2017 CSpace - Powered by
CSpace