Open Access
ARTICLE
Peizhu Gong, Jin Liu*, Shiqi Lv
Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 155-163, 2020, DOI:10.32604/jihpp.2020.010453
Abstract Image denoising is often used as a preprocessing step in computer
vision tasks, which can help improve the accuracy of image processing models.
Due to the imperfection of imaging systems, transmission media and recording
equipment, digital images are often contaminated with various noises during
their formation, which troubles the visual effects and even hinders people’s
normal recognition. The pollution of noise directly affects the processing of
image edge detection, feature extraction, pattern recognition, etc., making it
difficult for people to break through the bottleneck by modifying the model.
Many traditional filtering methods have shown poor performance since they do
not… More >
Open Access
REVIEW
Dongfang Yu, Jinwei Wang*
Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 165-174, 2020, DOI:10.32604/jihpp.2020.010466
Abstract Chemical spectral analysis is contemporarily undergoing a revolution
and drawing much attention of scientists owing to machine learning algorithms, in
particular convolutional networks. Hence, this paper outlines the major machine
learning and especially deep learning methods contributed to interpret chemical
images, and overviews the current application, development and breakthrough in
different spectral characterization. Brief categorization of reviewed literatures is
provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra,
Micro-scope, Raman spectra, Photoluminescence spectrum. End with the
overview of existing circumstances in this research area, we provide unique insight
and promising directions for the chemical imaging field to fully couple… More >
Open Access
REVIEW
Siran Yin1,2, Leiming Yan1,2,*, Yuanmin Shi1,2, Yaoyang Hou1,2, Yunhong Zhang1,2
Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 175-185, 2020, DOI:10.32604/jihpp.2020.010780
Abstract Deep learning based on neural networks has made new progress in a
wide variety of domain, however, it is lack of protection for sensitive
information. The large amount of data used for training is easy to cause leakage
of private information, thus the attacker can easily restore input through the
representation of latent natural language. The privacy preserving deep learning
aims to solve the above problems. In this paper, first, we introduce how to reduce
training samples in order to reduce the amount of sensitive information, and then
describe how to unbiasedly represent the data with respect to specific attributes,… More >
Open Access
ARTICLE
Xingxing Cao1, Liming Jiang1,*, Xiaoliang Wang1, Frank Jiang2
Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 187-197, 2020, DOI:10.32604/jihpp.2020.016243
Abstract Due to the lack of consideration of movement behavior information
other than time and location perception in current location prediction methods,
the movement characteristics of trajectory data cannot be well expressed, which
in turn affects the accuracy of the prediction results. First, a new trajectory data
expression method by associating the movement behavior information is given.
The pre-association method is used to model the movement behavior information
according to the individual movement behavior features and the group movement
behavior features extracted from the trajectory sequence and the region. The
movement behavior features based on pre-association may not always be the… More >
Open Access
ARTICLE
Qianqian Li1, Meng Li2, Lei Guo3,*, Zhen Zhang4
Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 199-205, 2020, DOI:10.32604/jihpp.2020.016299
Abstract On-site programming big data refers to the massive data generated in the
process of software development with the characteristics of real-time, complexity
and high-difficulty for processing. Therefore, data cleaning is essential for on-site
programming big data. Duplicate data detection is an important step in data
cleaning, which can save storage resources and enhance data consistency. Due to
the insufficiency in traditional Sorted Neighborhood Method (SNM) and the
difficulty of high-dimensional data detection, an optimized algorithm based on
random forests with the dynamic and adaptive window size is proposed. The
efficiency of the algorithm can be elevated by improving the method… More >
Login
Register
Submit a Paper
Propose a Special lssue