中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究... [38]
长春光学精密机械与... [13]
自动化研究所 [10]
沈阳自动化研究所 [10]
合肥物质科学研究院 [7]
西安光学精密机械研究... [7]
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采集方式
OAI收割 [152]
iSwitch采集 [7]
内容类型
期刊论文 [147]
会议论文 [9]
学位论文 [3]
发表日期
2018 [159]
学科主题
地球科学::地理学 [3]
Agricultur... [2]
Agricultur... [1]
Astronomy ... [1]
Automation... [1]
Ecology [1]
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浏览/检索结果:
共159条,第1-10条
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发表日期:2018
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GPU-based distortion correction for CMOS positioning camera using star point measurement
会议论文
OAI收割
Chongqing, China, 2018-12-14
作者:
Bu, Fan
;
Yao, Dalei
;
Qiu, Yuehong
;
Cao, Weicheng
;
Wang, Li
  |  
收藏
  |  
浏览/下载:57/0
  |  
提交时间:2019/07/22
Sensitivity of simulated crop yield and nitrate leaching of the wheat-maize cropping system in the North China Plain to model parameters
期刊论文
OAI收割
AGRICULTURAL AND FOREST METEOROLOGY, 2018, 卷号: 263, 页码: 25-40
作者:
Jabloun, Mohamed
;
Li, Xiaoxin
;
Zhang, Xiying
;
Tao, Fulu
;
Hu, Chunsheng
  |  
收藏
  |  
浏览/下载:49/0
  |  
提交时间:2019/05/23
Morris sensitivity analysis
Crop modelling
RDAISY toolbox
Crop yield
Nitrogen leaching
Wheat - maize cropping system
Preoperative radiomics nomogramfor microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
期刊论文
OAI收割
European Raidology, 2018, 期号: 1, 页码: 11
作者:
Ma Xiaohong
;
Wei Jingwei
;
Gu Dongsheng
;
Zhu Yongjian
;
Feng Bing
  |  
收藏
  |  
浏览/下载:72/0
  |  
提交时间:2019/05/08
Hepatocellular Carcinoma
Microvessel
Forecasting
Imaging
Three-dimensional Tomography
Shake Table Modeling of Pile Foundation Performance in Laterally Spreading Frozen Ground Crust Overlying Liquefiable Soils
期刊论文
iSwitch采集
JOURNAL OF COLD REGIONS ENGINEERING, 2018, 卷号: 32, 期号: 4, 页码: 9
作者:
Yang, Zhaohui Joey
;
Zhang, Xiaoyu Ryan
;
Yang, Runlin
;
Zhou, Xiaomin
;
Niu, Fujun
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2019/10/09
Pile foundation
Frozen ground
Liquefaction
Shake table experiment
Lateral spread
A single-image linear calibration method for camera
期刊论文
OAI收割
MEASUREMENT, 2018, 卷号: 130, 页码: 298-305
作者:
Zhang, Zhuang
;
Zhao, Rujin
;
Liu, Enhai
;
Yan, Kun
;
Ma, Yuebo
  |  
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2019/08/23
Camera calibration
Lens distortion correction
Division model
Non-iterative
Towards a new image processing system at Wendelstein 7-X: From spatial calibration to characterization of thermal events
期刊论文
OAI收割
REVIEW OF SCIENTIFIC INSTRUMENTS, 2018, 卷号: 89, 期号: 12, 页码: 10
作者:
Pisano, F.
;
Cannas, B.
;
Jakubowski, M. W.
;
Niemann, H.
;
Sitjes, A. Puig
  |  
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2020/03/31
Estimating Sink Parameters of Stochastic Functional-Structural Plant Models Using Organic Series-Continuous and Rhythmic Development
期刊论文
OAI收割
FRONTIERS IN PLANT SCIENCE, 2018, 卷号: 9, 页码: 17
作者:
Kang, Mengzhen
;
Hua, Jing
;
Wang, Xiujuan
;
de Reffye, Philippe
;
Jaeger, Marc
  |  
收藏
  |  
浏览/下载:31/0
  |  
提交时间:2019/07/12
greenlab
inverse method
source-sink parameters
functional-structural plant model
stochastic development
parameter estimation
Improving PM2.5 Forecasting and Emission Estimation Based on the Bayesian Optimization Method and the Coupled FLEXPART-WRF Model
期刊论文
OAI收割
ATMOSPHERE, 2018, 卷号: 9, 期号: 11, 页码: 17
作者:
Guo, Lifeng
;
Chen, Baozhang
;
Zhang, Huifang
;
Xu, Guang
;
Lu, Lijiang
  |  
收藏
  |  
浏览/下载:131/0
  |  
提交时间:2019/05/23
PM2
5
FLEXPART-WRF
real-time concentrations
inventory
Bayesian optimization method
Development of the Active Correlation Method: Theoretical-Methodological Aspect
期刊论文
OAI收割
PHYSICS OF PARTICLES AND NUCLEI, 2018, 卷号: 49, 页码: 1036-1045
作者:
Tsyganov, Yu. S.
;
Polyakov, A. N.
;
Kazacha, V. I.
;
Schlattauer, L.
;
Zhang, Z.
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2019/03/27
Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer
期刊论文
OAI收割
Radiotherapy and Oncology, 2018, 期号: 132, 页码: 171-177
作者:
Wang, Shuo
;
Liu, Zhenyu
;
Rong, Yu
;
Zhou, Bin
;
Bai, Yan
  |  
收藏
  |  
浏览/下载:50/0
  |  
提交时间:2019/04/30
Deep Learning
High-grade Serous Ovarian Cancer
Recurrence
Prognosis
Computed Tomography
Artificial Intelligence
Semi-supervised Learning
Auto Encoder
Unsupervised Learning