P
Peng Li
Researcher at North China Electric Power University
Publications - 45
Citations - 912
Peng Li is an academic researcher from North China Electric Power University. The author has contributed to research in topics: Secret sharing & Visual cryptography. The author has an hindex of 16, co-authored 44 publications receiving 681 citations. Previous affiliations of Peng Li include Harbin Institute of Technology & Capital Normal University.
Papers
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Journal ArticleDOI
Essential secret image sharing scheme with different importance of shadows
TL;DR: This paper considers the (t, s, k, n) essential SIS (ESIS) scheme, which encrypts a secret image into n shadow images and needs k shadows, which should include at least t essential shadows.
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Over-expression of the MxIRT1 gene increases iron and zinc content in rice seeds.
Song Tan,Rui Han,Peng Li,Peng Li,Guang Yang,Shuang Li,Peng Zhang,Wei-Bing Wang,Wei-Zhong Zhao,Li-Ping Yin +9 more
TL;DR: MxIRT1 transgenic tobacco-cultured bright yellow-2 cells and rice lines were subjected to different Fe conditions and the results from the non-invasive micro-test technique showed that iron was actively transported compared to cadmium as long as iron was readily available in the environment, suggesting that MxIRT 1 is a good candidate gene for plant Fe and Zn biofortification.
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Improvements of a two-in-one image secret sharing scheme based on gray mixing model
TL;DR: This paper can gain the lossless secret image and meantime enhance the contrast of previewed image, and introduces a new definition of contrast to evaluate the visual quality of the Previewed image.
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Characterization and expression of a high-affinity nitrate system transporter gene (TaNRT2.1) from wheat roots, and its evolutionary relationship to other NTR2 genes §
TL;DR: Alignment and comparative analyses of the deduced amino acid sequence from TaNRT2.1 cDNA indicated that this gene encodes a member of the HATS family, and expression patterns suggest it may be a candidate gene of the inducible HATS (iHATS) gene family.
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Reducing shadow size in essential secret image sharing by conjunctive hierarchical approach
TL;DR: This paper proposes a ( t, s, k , n )-ESIS scheme to achieve the less size of total shadow images and theLess size of required shadow images in reconstruction when compared with Li et al.