A review of android malware detection approaches based on machine learning
K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …
malware is also emerging in an endless stream. Many researchers have studied the …
Deep learning based detection and analysis of COVID-19 on chest X-ray images
Covid-19 is a rapidly spreading viral disease that infects not only humans, but animals are
also infected because of this disease. The daily life of human beings, their health, and the …
also infected because of this disease. The daily life of human beings, their health, and the …
Classification of the COVID-19 infected patients using DenseNet201 based deep transfer learning
Deep learning models are widely used in the automatic analysis of radiological images.
These techniques can train the weights of networks on large datasets as well as fine tuning …
These techniques can train the weights of networks on large datasets as well as fine tuning …
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …
researchers can employ several statistical rates, accordingly to the goal of the experiment …
Towards aircraft maintenance metaverse using speech interactions with virtual objects in mixed reality
A Siyaev, GS Jo - Sensors, 2021 - mdpi.com
Metaverses embedded in our lives create virtual experiences inside of the physical world.
Moving towards metaverses in aircraft maintenance, mixed reality (MR) creates enormous …
Moving towards metaverses in aircraft maintenance, mixed reality (MR) creates enormous …
Log-based anomaly detection with deep learning: How far are we?
Software-intensive systems produce logs for troubleshooting purposes. Recently, many
deep learning models have been proposed to automatically detect system anomalies based …
deep learning models have been proposed to automatically detect system anomalies based …
Customer churn prediction system: a machine learning approach
The customer churn prediction (CCP) is one of the challenging problems in the telecom
industry. With the advancement in the field of machine learning and artificial intelligence, the …
industry. With the advancement in the field of machine learning and artificial intelligence, the …
[HTML][HTML] The impact of class imbalance in classification performance metrics based on the binary confusion matrix
A major issue in the classification of class imbalanced datasets involves the determination of
the most suitable performance metrics to be used. In previous work using several examples …
the most suitable performance metrics to be used. In previous work using several examples …
Integrated intelligent fault diagnosis approach of offshore wind turbine bearing based on information stream fusion and semi-supervised learning
Offshore wind turbines play a vital role in transferring wind energy to electricity, which could
help relieve the energy crisis and improve the global climate. In general, offshore wind …
help relieve the energy crisis and improve the global climate. In general, offshore wind …