Engineers at eBay utilize robust methods in monitoring IT system signals for anomalies.
However, the growing scale of signals, both in volumes and dimensions, overpowers …

This paper proposes a new large-scale dataset called" ToyADMOS2" for anomaly detection
in machine operating sounds (ADMOS). As did for our previous ToyADMOS dataset, we …

Tiny Machine Learning (TinyML) is an emerging concept that concerns the execution of ML
tasks on very constrained IoT devices. Although TinyML has generated a strong R&D …

Anomalous sound detection (ASD) is the task of identifying whether the sound emitted from
an object is normal or anomalous. In some cases, early detection of this anomaly can …

With the development of multi-modal man-machine interaction, audio signal analysis is
gaining importance in a field traditionally dominated by video. In particular, anomalous …

Temporal video segmentation is the get-to-go automatic video analysis, which decomposes
a long-form video into smaller components for the following-up understanding tasks. Recent …

In industrial applications, the early detection of malfunctioning factory machinery is crucial. In
this paper, we consider acoustic malfunction detection via transfer learning. Contrary to the …

With the emergence of new digital technologies, a significant surge has been seen in the
volume of multimedia data generated from various smart devices. Several challenges for …

In this paper, a self-supervised representation learning method is proposed for anomalous
sound detection (ASD). ASD has received much research attention in recent DCASE …

This paper considers the problem of anomaly detection in an outdoor environment where
surveillance cameras are usually installed to monitor activities of general public. A novel …