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CASIA OpenIR
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A novel infrared spectral preprocessing method based on self-deconvolution and differentiation in the frequency domain 期刊论文
VIBRATIONAL SPECTROSCOPY, 2023, 卷号: 127, 页码: 11
作者:  Shan, Peng;  Liu, Junyi;  He, Zhonghai;  Peng, Silong;  Wang, Fei;  Liu, Chengzhao;  Zhou, Zheng
收藏  |  浏览/下载：130/0  |  提交时间：2023/11/17
Spectral preprocessing  Quantitative analysis  Fourier transform Infrared spectroscopy  
Unsupervised model adaptation for multivariate calibration by domain adaptation-regularization based kernel partial least square 期刊论文
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2023, 卷号: 292, 页码: 17
作者:  Shan, Peng;  Bi, Yiming;  Li, Zhigang;  Wang, Qiaoyun;  He, Zhonghai;  Zhao, Yuhui;  Peng, Silong
收藏  |  浏览/下载：59/0  |  提交时间：2023/11/17
Model adaptation  Domain-invariant feature representation  Projected maximum mean discrepancy  Kernel partial least squares  
RSDet++: Point-based modulated loss for more accurate rotated object detection 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 卷号: 32, 期号: 11, 页码: 7869-7879
作者:  Wen Qian;  Xue Yang;  Silong Peng;  Xiujuan Zhang;  Junchi Yan
Adobe PDF(6998Kb)  |  收藏  |  浏览/下载：186/64  |  提交时间：2023/06/07
Principal component analysis or kernel principal component analysis based joint spectral subspace method for calibration transfer 期刊论文
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2020, 卷号: 227, 页码: 16
作者:  Shan, Peng;  Zhao, Yuhui;  Wang, Qiaoyun;  Ying, Yao;  Peng, Silong
收藏  |  浏览/下载：208/0  |  提交时间：2020/03/30
Calibration transfer  Principal component analysis (PCA)  Kernel principal component analysis (KPCA)  Multivariate calibration  Joint spectral subspace  Partial least squares (PLS)  
Stacked ensemble extreme learning machine coupled with Partial Least Squares-based weighting strategy for nonlinear multivariate calibration 期刊论文
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2019, 卷号: 215, 页码: 97-111
作者:  Shan, Peng;  Zhao, Yuhui;  Wang, Qiaoyun;  Sha, Xiaopeng;  Lv, Xiaoyong;  Peng, Silong;  Ying, Yao
收藏  |  浏览/下载：187/0  |  提交时间：2019/12/16
Extreme learning machine (ELM)  Partial least squares (PLS)  Nonlinear multivariate calibration  Stacked generalization  
Calibration Transfer Based on Affine Invariance for NIR without Transfer Standards 期刊论文
MOLECULES, 2019, 卷号: 24, 期号: 9, 页码: 19
作者:  Zhao, Yuhui;  Zhao, Ziheng;  Shan, Peng;  Peng, Silong;  Yu, Jinlong;  Gao, Shuli
收藏  |  浏览/下载：219/0  |  提交时间：2019/09/30
near-infrared (NIR) spectroscopy  calibration transfer  affine invariance  multivariate calibration  partial least squares (PLS)  
An improved weighted multiplicative scatter correction algorithm with the use of variable selection: Application to near-infrared spectra 期刊论文
Chemometrics and Intelligent Laboratory Systems, 2019, 期号: 185, 页码: 114-121
作者:  Yifan Wu;  Silong Peng;  Qiong Xie;  Quanjie Han;  Genwei Zhang;  Haigang Sun
浏览  |  Adobe PDF(1486Kb)  |  收藏  |  浏览/下载：269/64  |  提交时间：2019/04/29
Multiplicative Scatter Correction  Weighted Least Squares  Variable Selection  Model Population Analysis  
Nonlinear least squares with local polynomial interpolation for quantitative analysis of IR spectra 期刊论文
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2019, 卷号: 206, 页码: 147-153
作者:  Wu, Yifan;  Peng, Silong;  Xie, Qiong;  Xu, Pengcheng
浏览  |  Adobe PDF(1404Kb)  |  收藏  |  浏览/下载：323/86  |  提交时间：2019/04/29
Spectroscopy  Quantitative analysis  Nonlinear least squares  Local polynomial interpolation  
Simultaneous spectrum fitting and baseline correction using sparse representation 期刊论文
Analyst, 2017, 期号: 142, 页码: 2460-2468
作者:  Han QJ(韩权杰);  Xie Q(谢琼);  Peng SL(彭思龙);  Guo BK(郭宝奎)
Adobe PDF(2092Kb)  |  收藏  |  浏览/下载：247/71  |  提交时间：2019/04/24
Sparse Representation  Spectrum Fitting  Baseline Correction  
Simultaneous spectrum fitting and baseline correction using sparse representation 期刊论文
ANALYST, 2017, 卷号: 142, 期号: 13, 页码: 2460-2468
作者:  Han, Quanjie;  Xie, Qiong;  Peng, Silong;  Guo, Baokui
Adobe PDF(2058Kb)  |  收藏  |  浏览/下载：372/98  |  提交时间：2017/09/12
Sparse Representation