AIMC Topic: Data Collection

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Lightweight On-Device Detection of Android Malware Based on the Koodous Platform and Machine Learning.

Sensors (Basel, Switzerland)
Currently, Android is the most popular operating system among mobile devices. However, as the number of devices with the Android operating system increases, so does the danger of using them. This is especially important as smartphones increasingly au...

A Machine Learning Approach to Improve Ranging Accuracy with AoA and RSSI.

Sensors (Basel, Switzerland)
Ranging accuracy is a critical parameter in time-based indoor positioning systems. Indoor environments often have complex structures, which make centimeter-level-accurate ranging a challenging task. This study proposes a new distance measurement meth...

A Comparison on LSTM Deep Learning Method and Random Walk Model Used on Financial and Medical Applications: An Example in COVID-19 Development Prediction.

Computational intelligence and neuroscience
This study aims to establish the model of the cryptocurrency price trend based on a financial theory using the Long Short-Term Memory (LSTM) networks model with multiple combinations between the window length and the predicting horizons. The Random W...

A data-centric weak supervised learning for highway traffic incident detection.

Accident; analysis and prevention
Using the data from loop detector sensors for near-real-time detection of traffic incidents on highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leverag...

How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow? A technography study in 2021.

European radiology
OBJECTIVES: How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow?

Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information.

Sensors (Basel, Switzerland)
The deterioration of infrastructure's health has become more predominant on a global scale during the 21st century. Aging infrastructure as well as those structures damaged by natural disasters have prompted the research community to improve state-of...

Convolution neural network with batch normalization and inception-residual modules for Android malware classification.

Scientific reports
Deep learning technology is changing the landscape of cybersecurity research, especially the study of large amounts of data. With the rapid growth in the number of malware, developing of an efficient and reliable method for classifying malware has be...

GLD-Net: Deep Learning to Detect DDoS Attack via Topological and Traffic Feature Fusion.

Computational intelligence and neuroscience
Distributed denial of service (DDoS) attacks are the most common means of cyberattacks against infrastructure, and detection is the first step in combating them. The current DDoS detection mainly uses the improvement or fusion of machine learning and...

Analysis of e-Mail Spam Detection Using a Novel Machine Learning-Based Hybrid Bagging Technique.

Computational intelligence and neuroscience
e-mail service providers and consumers find it challenging to distinguish between spam and nonspam e-mails. The purpose of spammers is to spread false information by sending annoying messages that catch the attention of the public. Various spam ident...

Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning.

Sensors (Basel, Switzerland)
Risky driving behavior seriously affects the driver's ability to react, execute and judge, which is one of the major causes of traffic accidents. The timely and accurate identification of the driving status of drivers is particularly important, since...