Open Access
ARTICLE
Jianquan Ouyang*, Yi He, Huanrong Tang, Zhousong Fu
Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 1-9, 2020, DOI:10.32604/jihpp.2020.010657
Abstract Cryo-em (Cryogenic electron microscopy) is a technology this can
build bio-macromolecule of three-dimensional structure. Under the condition of
now, the projection image of the biological macromolecule which is collected by
the Cryo-em technology that the contrast is low, the signal to noise is low, image
blurring, and not easy to distinguish single particle from background, the
corresponding processing technology is lagging behind. Therefore, make Cryoem image denoising useful, and maintaining bio-macromolecule of contour or
signal of function-construct improve Cryo-em image quality or resolution of
Cryo-em three-dimensional structure have important effect. This paper
researched a denoising function base on GANs (generative… More >
Open Access
ARTICLE
Xuefei Du*, Xuyu Xiang
Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 11-19, 2020, DOI:10.32604/jihpp.2020.010114
Abstract Citrus anthracnose is a common fungal disease in citrus-growing areas
in China, which causes very serious damage. At present, the manual management
method is time-consuming and labor-consuming, which reduces the control
effect of citrus anthracnose. Therefore, by designing and running the image
retrieval system of citrus anthracnose, the automatic recognition and analysis of
citrus anthracnose control were realized, and the control effect of citrus
anthracnose was improved. In this paper, based on the self-collected and collated
citrus anthracnose image database, we use three image features to realize an
image retrieval system based on citrus anthracnose through SMV, AP clustering
optimization.… More >
Open Access
REVIEW
Meigui Zhang*, Kehui Zeng, Jinwei Wang
Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 21-34, 2020, DOI:10.32604/jihpp.2020.010467
Abstract The development of artificial intelligence makes the application of face
recognition more and more extensive, which also leads to the security of face
recognition technology increasingly prominent. How to design a face anti-spoofing
method with high accuracy, strong generalization ability and meeting practical needs
is the focus of current research. This paper introduces the research progress of face
anti-spoofing algorithm, and divides the existing face anti-spoofing methods into two
categories: methods based on manual feature expression and methods based on deep
learning. Then, the typical algorithms included in them are classified twice, and the
basic ideas, advantages and disadvantages of… More >
Open Access
ARTICLE
Zaoyu Wei1,*, Jiaqi Wang2, Xueqi Shen1, Qun Luo1
Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 35-45, 2020, DOI:10.32604/jihpp.2020.010331
Abstract Smart contract has greatly improved the services and capabilities of
blockchain, but it has become the weakest link of blockchain security because of
its code nature. Therefore, efficient vulnerability detection of smart contract is the
key to ensure the security of blockchain system. Oriented to Ethereum smart
contract, the study solves the problems of redundant input and low coverage in the
smart contract fuzz. In this paper, a taint analysis method based on EVM is
proposed to reduce the invalid input, a dangerous operation database is designed
to identify the dangerous input, and genetic algorithm is used to optimize the… More >
Open Access
REVIEW
Jiawei Zhang*, Jinwei Wang
Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 47-57, 2020, DOI:10.32604/jihpp.2020.010462
Abstract In recent years, deep learning has become a hotspot and core method in
the field of machine learning. In the field of machine vision, deep learning has
excellent performance in feature extraction and feature representation, making it
widely used in directions such as self-driving cars and face recognition. Although
deep learning can solve large-scale complex problems very well, the latest
research shows that the deep learning network model is very vulnerable to the
adversarial attack. Add a weak perturbation to the original input will lead to the
wrong output of the neural network, but for the human eye, the difference… More >
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