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CAS IR Grid
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国家天文台 [13]
自动化研究所 [10]
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长春应用化学研究所 [2]
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OAI收割 [31]
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期刊论文 [25]
学位论文 [4]
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Classification of 2D Stellar Spectra Based on FFCNN
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 卷号: 42, 期号: 6, 页码: 1881-1885
作者:
Lu Ya-kun
;
Qiu Bo
;
Luo A-li
;
Guo Xiao-yu
;
Wang Lin-qian
  |  
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2022/09/19
Two-dimensional stellar spectra
Spectral classification
FFCNN model
Normalized
Cross-validation
Research on the Improvement of Spectra Classification Performance With the High-Performance Hybrid Deep Learning Network
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 卷号: 42, 期号: 3, 页码: 699-703
作者:
Liu Zhong-bao
;
Wang Jie
;
Wang J(王杰)
  |  
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2022/07/28
Spectra classification
Deep learning network
BERT model
CNN model
Application of NIR Spectroscopy in Explosive Powder Surface Contamination Remote Detection
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 卷号: 41
作者:
Li Da-cheng
;
Wang An-jing
;
Li Yang-yu
;
Cui Fang-xiao
;
Wu Jun
  |  
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2021/04/26
NIR Spectra
Explosive powder
Surface contamination
Classification
Stellar Spectra Classification by Support Vector Machine with Unlabeled Data
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 卷号: 39, 期号: 3, 页码: 948-952
作者:
Zhang Jing
;
Tu Liang-ping
;
Wang Jie
;
Liu Zhong-bao
;
Lei Yu-fei
  |  
收藏
  |  
浏览/下载:60/0
  |  
提交时间:2019/05/23
Stellar spectra
Intelligent classification
Twin support vector machine
Unlabeled data
Stellar Spectra Classification with Entropy-Based Learning Machine
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 卷号: 38, 期号: 2, 页码: 660-664
作者:
Liu Zhong-bao
;
Fu Li-zhen
;
Ren Juan-juan
;
Song Wen-ai
;
Kong Xiao
  |  
收藏
  |  
浏览/下载:39/0
  |  
提交时间:2018/06/08
Data Mining
Stellar Spectra Classification
Entropy
Sloan Digital Sky Survey (Sdss)
An Automated Stellar Spectra Classification System Basing on Non-Parameter Regression and Adaboost
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 卷号: 37, 期号: 5, 页码: 1555-1559
作者:
Liu Rong
;
Qiao Xue-jun
;
Zhang Jian-nan
;
Duan Fu-qing
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2017/09/01
Spectra classification
Adaboost
Non-parameter regression
Luminosity
Distinguishing the Rare Spectra with the Unbalanced Classification Method Based on Mutual Information
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 卷号: 36, 期号: 11, 页码: 3746-3751
作者:
Liu Zhong-bao
;
Ren Juan-juan
;
Kong Xiao
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2017/03/01
Unbalanced classification
Mutual information
Rare spectra
Decision tree
A New Distance Metric between Different Stellar Spectra: the Residual Distribution Distance
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 卷号: 35, 期号: 12, 页码: 3524-3528
作者:
Liu Jie
;
Pan Jing-chang
;
Luo A-li
;
Wei Peng
;
Liu Meng
收藏
  |  
浏览/下载:113/0
  |  
提交时间:2016/11/08
Stellar spectra
Distance metric
Residual distribution
Stellar spectra classification
Stellar spctra clustering
Stellar parameter estimation
Spectra Classification Based on Local Mean-Based K-Nearest Centroid Neighbor Method
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 卷号: 35, 期号: 4, 页码: 1103-1106
作者:
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2016/11/11
Spectra classification
K-nearest neighbor
Nearest centroid neighborhood
K-nearest centroid neighbor
Qualitative determination of the components of textile products using near infrared spectroscopy (EI CONFERENCE)
会议论文
OAI收割
International Symposium on Photonics and Optoelectronics, SOPO 2010, June 19, 2010 - June 21, 2010, Chengdu, China
作者:
Chen X.
;
Chen X.
;
Chen X.
;
Wang D.
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2013/03/25
In the paper
A total of 40 pure or two-mixed textile weaves were prepared and classification of these samples was introduced using near infrared spectroscopy (NIRS)
all textile samples are selected among four classes
which are Cotton-Terylene
Cotton-Polyurethane
Cotton and Terylene
according to theirs components. Near infrared diffuse reflectance spectra of the samples were collected
Mahalanobis distance was used to discriminate the samples coupled with principle components analysis (PCA)
the results showed that near infrared spectroscopy could determine which class one textile weave belongs to easily comparing with traditional methods. In addition
the expectation of the further research on qualitative determination of textile products by NIR technology was discussed in the end of this paper. 2010 IEEE.