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8篇 您的检索式:作者名="DENG Dexiang"
    题名 作者 年代 出处 被引量
1Fabric Defect Detection Using Independent Component Analysis and Phase Congruency显示文摘A novel method based on independent component analysis and phase congruency is proposed for detecting defects in textile fabric images. By independent component, we can obtain textile structural features of fabric-free images. By phase congruency, structure information is reduced, which can distinguish the defect region from the defect-free regions. Finally, we have the detecting result from binary image which is obtained by a threshold step. Compared with other algorithms, the proposed method not only has robustness with high detection rate, but also detects various types of defects quite well.LENG Qiujun ZHANG Hu FAN Cien DENG Dexiang 2014Wuhan University Journal of Natural Sciences2014,19,4:7
2Blockcompressed sensing of multispectral remote sensingimage by adaptive filtering prediction 显示文摘Wang Xuan Shi Wenxuan Deng Dexiang 2013IJACT :International Journal of Advancements in ComputingTechnology2013,5,6:1
3Quantitative trait locus mapping of resistance to Aspergillus flavus infection using a recombinant inbred line population in maize显示文摘Zhitong Yin Yanqiu Wang Feifei Wu Xiao Gu Yunlong Bian Yijun Wang Dexiang Deng 2014Molecular Breeding2014,,1:1
4A self-adaptive and real-time panoramic video mosaicing system 显示文摘ZENG Lin DENG Dexiang CHEN Xi 2012Journal of computers2012,7,1:1
5Genome-wide analysis of primary auxin-responsive Aux/IAA gene family in maize (Zea mays. L.)显示文摘Yijun Wang Dexiang Deng Yunlong Bian Yanping Lv Qin Xie 2010Molecular Biology Reports2010,,8:1
6Genome-wide Association Analysis of Fast Chlorophyll Fluorescence Parameters in Maize显示文摘Fast chlorophyll fluorescence parameters are widely used to characterize the photosynthetic efficiency of plants. In this study,a genome-wide association analysis was used to detect key single-nucleotide polymorphisms( SNPs) associated with fast chlorophyll fluorescence parameters using more than 560 000 SNPs in a maize panel consisting of 404 inbred lines. In four field environments,41 SNPs were detected to be associated with five fast chlorophyll fluorescence parameters,including ABS / CS_o,ET_o/ CS_o,TR_o/ ABS,ET_o/ TRoand PIcs. Among these identified SNPs,8,6,18,4 and 5 were significantly associated with ET_o/ TR_o,ABS/CS_o,TRo/ ABS,ET_o/ CS_oand PIcs,respectively. These SNPs will help to discover genes for chlorophyll fluorescence parameters,better understand the genetic basis of photosynthesis,and assist in developing marker-assisted selection breeding programs in maize.Zhitong YIN Qiuxia QIN Xin KAN Yanan CHEN Qian CHENG Dexiang DENG 2016Agricultural Biotechnology2016,5,6:1
7Impact of climate warming on crop planting and production in Northwest China显示文摘Deng Zhenyong Zhang Qiang Pu Jinyong Liu Dexiang Guo Hui Wang Quanfu Zhao Hong Wang Heling 2008Acta Ecologica Sinica2008,,8:1
8Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks显示文摘Non-orthogonal multiple access(NOMA)is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner.NOMA allows multiple terminals to share the same resource unit at the same time.The receiver usually needs to configure successive interference cancellation(SIC).The receiver eliminates co-channel interference(CCI)between users and it can significantly improve the system throughput.In order to meet the demands of users and improve fairness among them,this paper proposes a new power allocation scheme.The objective is to maximize user fairness by deploying the least fairness in multiplexed users.However,the objective function obtained is non-convex which is converted into convex form by utilizing the optimal Karush-Kuhn-Tucker(KKT)constraints.Simulation results show that the proposed power allocation scheme gives better performance than the existing schemes which indicates the effectiveness of the proposed scheme.Jianzhong Li Dexiang Mei Dong Deng Imran Khan Peerapong Uthansakul 2020Computers, Materials & Continua2020,,11:0
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