What is it about?
With the number of end devices increasing anomaly detection becomes an important task in computer systems. We use different image representations and an object detection model called YOLO in order to precisely localize and classify anomalies in time series data.
Featured Image
Why is it important?
In this paper, we study the performance of time-series to image transformation techniques combined with machine vision and show that: a) we can not only describe and classify, but also precisely localize link layer anomalies in wireless networks and b) the classification scores of the method are comparable with state of the art classifiers.
Perspectives
Writing this article was an amazing learning experience, as I learned a lot about not only time series, object detection and deep learning but also research work in general. Working with co-authors was a great pleasure, as they were always open for a colorful discussion about the subject.
Valerij Jovanov
Jožef Stefan Institute
Read the Original
This page is a summary of: Machine Vision Based Wireless Link Layer Anomaly Characterization, June 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3597062.3597283.
You can read the full text:
Contributors
The following have contributed to this page
