Big data processing architecture for radio signals empowered by deep learning: Concept, experiment, applications and challenges
S Zheng, S Chen, L Yang, J Zhu, Z Luo, J Hu… - IEEE …, 2018 - ieeexplore.ieee.org
In modern society, the demand for radio spectrum resources is increasing. As the
information carriers of wireless transmission data, radio signals exhibit the characteristics of …
information carriers of wireless transmission data, radio signals exhibit the characteristics of …
Machine learning based big data processing framework for cancer diagnosis using hidden Markov model and GM clustering
G Manogaran, V Vijayakumar, R Varatharajan… - Wireless personal …, 2018 - Springer
The change in the DNA is a form of genetic variation in the human genome. In addition, the
DNA copy number change is also linked with the progression of many emerging diseases …
DNA copy number change is also linked with the progression of many emerging diseases …
A novel fractional order model for state of charge estimation in lithium ion batteries
Battery models are the cornerstone to battery state of charge (SOC) estimation and battery
management systems in electric vehicles. This paper proposes a novel fractional-order …
management systems in electric vehicles. This paper proposes a novel fractional-order …
[HTML][HTML] A survey on machine learning-based mobile big data analysis: Challenges and applications
This paper attempts to identify the requirement and the development of machine learning-
based mobile big data (MBD) analysis through discussing the insights of challenges in the …
based mobile big data (MBD) analysis through discussing the insights of challenges in the …
Dynamic sign language recognition based on video sequence with BLSTM-3D residual networks
Y Liao, P Xiong, W Min, W Min, J Lu - IEEE Access, 2019 - ieeexplore.ieee.org
Sign language recognition aims to recognize meaningful movements of hand gestures and
is a significant solution in intelligent communication between the deaf community and …
is a significant solution in intelligent communication between the deaf community and …
Multiple feature reweight densenet for image classification
K Zhang, Y Guo, X Wang, J Yuan, Q Ding - IEEE Access, 2019 - ieeexplore.ieee.org
Recent network research has demonstrated that the performance of convolutional neural
networks can be improved by introducing a learning block that captures spatial correlations …
networks can be improved by introducing a learning block that captures spatial correlations …
Dual cross-entropy loss for small-sample fine-grained vehicle classification
Fine-grained vehicle classification is a challenging topic in computer vision due to the high
intraclass variance and low interclass variance. Recently, considerable progress has been …
intraclass variance and low interclass variance. Recently, considerable progress has been …
Decentralized big data auditing for smart city environments leveraging blockchain technology
H Yu, Z Yang, RO Sinnott - IEEE Access, 2018 - ieeexplore.ieee.org
The idea of big data has gained extensive attention from governments and academia all
over the world. It is especially relevant for the establishment of a smart city environment …
over the world. It is especially relevant for the establishment of a smart city environment …
Variational Bayesian learning for Dirichlet process mixture of inverted Dirichlet distributions in non-Gaussian image feature modeling
In this paper, we develop a novel variational Bayesian learning method for the Dirichlet
process (DP) mixture of the inverted Dirichlet distributions, which has been shown to be very …
process (DP) mixture of the inverted Dirichlet distributions, which has been shown to be very …
Deep learning based improved classification system for designing tomato harvesting robot
Maturity level-based classification system plays an essential role in the design of tomato
harvesting robot. Traditional knowledge-based systems are unable to meet the current …
harvesting robot. Traditional knowledge-based systems are unable to meet the current …