Open Access
ARTICLE
Dunhong Yao1,2,3,*, Yu Chen4
Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 59-65, 2020, DOI:10.32604/jihpp.2020.010223
Abstract With the rapid development of the Internet, many enterprises have
launched their network platforms. When users browse, search, and click the
products of these platforms, most platforms will keep records of these network
behaviors, these records are often heterogeneous, and it is called log data. To
effectively to analyze and manage these heterogeneous log data, so that
enterprises can grasp the behavior characteristics of their platform users in time,
to realize targeted recommendation of users, increase the sales volume of
enterprises’ products, and accelerate the development of enterprises. Firstly, we
follow the process of big data collection, storage, analysis, and… More >
Open Access
ARTICLE
Rongyu Chen, Lili Pan*, Yan Zhou, Qianhui Lei
Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 67-76, 2020, DOI:10.32604/jihpp.2020.010472
Abstract With the rapid development of information technology, the speed and
efficiency of image retrieval are increasingly required in many fields, and a
compelling image retrieval method is critical for the development of information.
Feature extraction based on deep learning has become dominant in image retrieval
due to their discrimination more complete, information more complementary and
higher precision. However, the high-dimension deep features extracted by CNNs
(convolutional neural networks) limits the retrieval efficiency and makes it difficult
to satisfy the requirements of existing image retrieval. To solving this problem, the
high-dimension feature reduction technology is proposed with improved CNN and
PCA… More >
Open Access
ARTICLE
Yan Zhou, Lili Pan*, Rongyu Chen, Weizhi Shao
Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 77-86, 2020, DOI:10.32604/jihpp.2020.010486
Abstract In large-scale image retrieval, deep features extracted by Convolutional
Neural Network (CNN) can effectively express more image information than those
extracted by traditional manual methods. However, the deep feature dimensions
obtained by Deep Convolutional Neural Network (DCNN) are too high and
redundant, which leads to low retrieval efficiency. We propose a novel image
retrieval method, which combines deep features selection with improved DCNN
and hash transform based on high-dimension features reduction to gain lowdimension deep features and realizes efficient image retrieval. Firstly, the
improved network is based on the existing deep model to build a more profound
and broader network… More >
Open Access
REVIEW
Xin Liu*, Xiao Chen
Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 87-94, 2020, DOI:10.32604/jihpp.2020.09839
Abstract In recent years, with the rapid growth of generative adversarial
networks (GANs), a photo-realistic face can be easily generated from a random
vector. Moreover, the faces generated by advanced GANs are very realistic. It is
reasonable to acknowledge that even a well-trained viewer has difficulties to
distinguish artificial from real faces. Therefore, detecting the face generated by
GANs is a necessary work. This paper mainly introduces some methods to detect
GAN-generated fake faces, and analyzes the advantages and disadvantages of
these models based on the network structure and evaluation indexes, and the
results obtained in the respective data sets. On… More >
Open Access
ARTICLE
Bingtao Hu*, Jinwei Wang
Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 95-105, 2020, DOI:10.32604/jihpp.2020.010464
Abstract With the development of computer graphics, realistic computer
graphics (CG) have become more and more common in our field of vision. This
rendered image is invisible to the naked eye. How to effectively identify CG and
natural images (NI) has been become a new issue in the field of digital forensics.
In recent years, a series of deep learning network frameworks have shown great
advantages in the field of images, which provides a good choice for us to solve
this problem. This paper aims to track the latest developments and applications
of deep learning in the field of CG and… More >
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