Mechanical fault diagnosis is one of the important technologies in the fourth industrial
revolution. In recent years, mechanical fault diagnosis based on audio signal analysis …

Anomaly detection (AD) plays a crucial role in various domains, including cybersecurity,
finance, and healthcare, by identifying patterns or events that deviate from normal …

Over the past few years, anomaly detection, a subfield of machine learning that is mainly
concerned with the detection of rare events, witnessed an immense improvement following …

With the recent advances in technology, a wide range of systems continue to collect a large
amount of data over time and thus generate time series. Time-Series Anomaly Detection …

Existing contrastive learning methods for anomalous sound detection refine the audio
representation of each audio sample by using the contrast between the samples' …

To ensure the reliable use and maintenance of a washing machine, condition monitoring
and detection of anomalous operations at an early stage are necessary. In this study, we …

One-Class anomaly detection aims to detect anomalies from normal samples using a model
trained on normal data. With recent advancements in deep learning, researchers have …

Failure prediction is key to ensuring the reliable operation of vehicles, especially for
organizations that depend on a fleet of vehicles. However, traditional approaches often rely …

Thanks to the development of deep learning, machine abnormal sound detection (MASD)
based on unsupervised learning has exhibited excellent performance. However, in the task …

This paper proposes an approach for anomalous sound detection that incorporates outlier
exposure and inlier modeling within a unified framework by multitask learning. While outlier …