A review on outlier/anomaly detection in time series data
Recent advances in technology have brought major breakthroughs in data collection,
enabling a large amount of data to be gathered over time and thus generating time series …
enabling a large amount of data to be gathered over time and thus generating time series …
[PDF][PDF] State of health prediction of lithium-ion batteries based on machine learning: Advances and perspectives
Accurate state of health (SOH) prediction is significant to guarantee operation safety and
avoid latent failures of lithium-ion batteries. With the development of communication and …
avoid latent failures of lithium-ion batteries. With the development of communication and …
Towards the deployment of machine learning solutions in network traffic classification: A systematic survey
F Pacheco, E Exposito, M Gineste… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Traffic analysis is a compound of strategies intended to find relationships, patterns,
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …
Machine learning for streaming data: state of the art, challenges, and opportunities
Incremental learning, online learning, and data stream learning are terms commonly
associated with learning algorithms that update their models given a continuous influx of …
associated with learning algorithms that update their models given a continuous influx of …
Spiking neural networks and online learning: An overview and perspectives
Applications that generate huge amounts of data in the form of fast streams are becoming
increasingly prevalent, being therefore necessary to learn in an online manner. These …
increasingly prevalent, being therefore necessary to learn in an online manner. These …
Incremental learning in online scenario
Modern deep learning approaches have achieved great success in many vision applications
by training a model using all available task-specific data. However, there are two major …
by training a model using all available task-specific data. However, there are two major …
A secure ai-driven architecture for automated insurance systems: Fraud detection and risk measurement
The private insurance sector is recognized as one of the fastest-growing industries. This
rapid growth has fueled incredible transformations over the past decade. Nowadays, there …
rapid growth has fueled incredible transformations over the past decade. Nowadays, there …
Data stream analysis: Foundations, major tasks and tools
The significant growth of interconnected Internet‐of‐Things (IoT) devices, the use of social
networks, along with the evolution of technology in different domains, lead to a rise in the …
networks, along with the evolution of technology in different domains, lead to a rise in the …
A review of automatic recognition technology for bird vocalizations in the deep learning era
Birds are considered critical indicators of ecosystem condition. Automatic recording devices
have emerged as a trending tool to assist field observations, contributing to biodiversity …
have emerged as a trending tool to assist field observations, contributing to biodiversity …
[HTML][HTML] A comparative study on online machine learning techniques for network traffic streams analysis
Modern networks generate a massive amount of traffic data streams. Analyzing this data is
essential for various purposes, such as network resources management and cyber-security …
essential for various purposes, such as network resources management and cyber-security …