中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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Lexicographic Multiobjective Scatter Search for the Optimization of Sequence-Dependent Selective Disassembly Subject to Multiresource Constraints 期刊论文  OAI收割
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 7, 页码: 3307-3317
作者:  
Guo XW(郭希旺);  Zhou MC(周孟初);  Liu SX(刘士新);  Qi, Liang
  |  收藏  |  浏览/下载:36/0  |  提交时间:2021/06/23
Alkaloid chemodiversity in Mandragora spp. is associated with loss-of-functionality of MoH6H, a hyoscyamine 6 beta-hydroxylase gene 期刊论文  OAI收割
PLANT SCIENCE, 2019, 卷号: 283, 页码: 301-310
作者:  
Schlesinger, Daniel;  Rikanati, Rachel Davidovich;  Volis, Sergei;  Faigenboim, Adi;  Vendramin, Vera
  |  收藏  |  浏览/下载:76/0  |  提交时间:2019/07/29
Multiple rules with game theoretic analysis for flexible flow shop scheduling problem with component altering times 期刊论文  OAI收割
International Journal of Modelling, Identification and Control, 2016, 卷号: 26, 期号: 1, 页码: 1-18
作者:  
Han ZH(韩忠华);  Zhu YX(朱一行);  Ma, Xiaofu;  Chen, Zhili
收藏  |  浏览/下载:35/0  |  提交时间:2016/08/13
Action dependent heuristic dynamic programming based residential energy scheduling with home energy inter-exchange 期刊论文  OAI收割
ENERGY CONVERSION AND MANAGEMENT, 2015, 卷号: 103, 页码: 553-561
作者:  
Xu, Yancai;  Liu, Derong;  Wei, Qinglai;  Qinglai Wei
收藏  |  浏览/下载:27/0  |  提交时间:2015/10/13
A MLP-PNN neural network for CCD image super-resolution in wavelet packet domain (EI CONFERENCE) 会议论文  OAI收割
2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, October 12, 2008 - October 14, 2008, Dalian, China
Zhao X.; Fu D.; Zhai L.
收藏  |  浏览/下载:70/0  |  提交时间:2013/03/25
Image super-resolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures  typically with high computational costs. In this paper is proposed a novel algorithm for super-resolution that enables a substantial decrease in computer load. First  decompose and reconstruct the image by wavelet packet. Before constructing the image  use neural network in place of other rebuilding method to reconstruct the coefficients in the wavelet packet domain. Second  probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data in the wavelet packet domain. The network kernel function is optimally determined for this problem by a MLP-PNN (Multi Layer Perceptron - Probabilistic Neural Network) trained on synthetic data. Network parameters dependent on the sequence noise level. This super-sampled image is spatially Altered to correct finite pixel size effects  to yield the final high-resolution estimate. This method can decrease the calculation cost and get perfect PSNR. Results are presented  showing the quality of the proposed method. 2008 IEEE.