Open Access
ARTICLE
Wei Fang1,2,*, Yupeng Chen1, Qiongying Xue1
Journal on Big Data, Vol.3, No.3, pp. 97-110, 2021, DOI:10.32604/jbd.2021.016993
Abstract In the past few years, deep learning has developed rapidly, and many
researchers try to combine their subjects with deep learning. The algorithm based
on Recurrent Neural Network (RNN) has been successfully applied in the fields
of weather forecasting, stock forecasting, action recognition, etc. because of its
excellent performance in processing Spatio-temporal sequence data. Among
them, algorithms based on LSTM and GRU have developed most rapidly
because of their good design. This paper reviews the RNN-based Spatiotemporal sequence prediction algorithm, introduces the development history of
RNN and the common application directions of the Spatio-temporal sequence
prediction, and includes precipitation nowcasting… More >
Open Access
ARTICLE
Yue Li, Jin Liu*, Shengjie Shang
Journal on Big Data, Vol.3, No.3, pp. 111-118, 2021, DOI:10.32604/jbd.2021.017169
Abstract Visual Question Answering (VQA) has attracted extensive research
focus and has become a hot topic in deep learning recently. The development of
computer vision and natural language processing technology has contributed to
the advancement of this research area. Key solutions to improve the performance
of VQA system exist in feature extraction, multimodal fusion, and answer
prediction modules. There exists an unsolved issue in the popular VQA image
feature extraction module that extracts the fine-grained features from objects of
different scale difficultly. In this paper, a novel feature extraction network that
combines multi-scale convolution and self-attention branches to solve the above… More >
Open Access
ARTICLE
Hengyang Wang, Jin Liu*, Haoliang Ren
Journal on Big Data, Vol.3, No.3, pp. 119-126, 2021, DOI:10.32604/jbd.2021.017184
Abstract The past decade has seen the rapid development of text detection based on
deep learning. However, current methods of Chinese character detection and
recognition have proven to be poor. The accuracy of segmenting text boxes in natural
scenes is not impressive. The reasons for this strait can be summarized into two points:
the complexity of natural scenes and numerous types of Chinese characters. In
response to these problems, we proposed a lightweight neural network architecture
named CTSF. It consists of two modules, one is a text detection network that
combines CTPN and the image feature extraction modules of PVANet, named… More >
Open Access
ARTICLE
Ying Zhou*, Weiwei Luo
Journal on Big Data, Vol.3, No.3, pp. 127-133, 2021, DOI:10.32604/jbd.2021.019236
Abstract In recent years, QR code has been widely used in the Internet and
mobile devices. It is based on open standards and easy to generate a code, which
lead to that anyone can generate their own QR code. Because the QR code does not
have the ability of information hiding, any device can access the content in QR
code. Thus, hiding the secret data in QR code becomes a hot topic. Previously, the
information hiding methods based on QR code all use the way of information
hiding based on image, mostly using digital watermarking technology, and not
using the coding… More >
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