Related papers: Comparison of Supervised and Unsupervised Anomaly …
Anomaly detection in images plays a significant role for many applications across all industries, such as disease diagnosis in healthcare or quality assurance in manufacturing. Manual inspection of images, when extended over a monotonously…
Image manipulation detection algorithms designed to identify local anomalies often rely on the manipulated regions being ``sufficiently'' different from the rest of the non-tampered regions in the image. However, such anomalies might not be…
We investigate unsupervised anomaly detection for high-dimensional data and introduce a deep metric learning (DML) based framework. In particular, we learn a distance metric through a deep neural network. Through this metric, we project the…
Autoencoder and its variants have been widely applicated in anomaly detection.The previous work memory-augmented deep autoencoder proposed memorizing normality to detect anomaly, however it neglects the feature discrepancy between different…
Anomalies can be defined as any non-random structure which deviates from normality. Anomaly detection methods reported in the literature are numerous and diverse, as what is considered anomalous usually varies depending on particular…
DEPFET active pixel sensors are a well-developed technology for vertex detectors at future colliders. Extensive test beam campaigns have proven the excellent performance of these devices, and their radiation hardness has been thoroughly…
In this paper, we proposed to investigate unsupervised anomaly detection in Synthetic Aperture Radar (SAR) images. Our approach considers anomalies as abnormal patterns that deviate from their surroundings but without any prior knowledge of…
We investigate the power of low-energy, high-luminosity electron--positron colliders to probe hidden sectors with a mass below ~10 GeV that couple to Standard Model particles through a light mediator. Such sectors provide well-motivated…
Many dark matter models generically predict invisible and displaced signatures at Belle II, but even striking events may be missed by the currently implemented search programme because of inefficient trigger algorithms. Of particular…
The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general…
Next-generation particle accelerators demand advanced beam-diagnostic capabilities to ensure high performance, operational reliability, and sustainable machine operation. Increasing beam intensities and stored energies make the precise…
Anomaly detection in medical imaging is to distinguish the relevant biomarkers of diseases from those of normal tissues. Deep supervised learning methods have shown potentials in various detection tasks, but its performances would be…
Anomaly detection relies on designing a score to determine whether a particular event is uncharacteristic of a given background distribution. One way to define a score is to use autoencoders, which rely on the ability to reconstruct certain…
In the minimal $U(1)$ extension of the Standard Model (SM), a new gauge boson referred to as "dark photon" is predicted. The dark-photon mass can be generated from an additional Higgs mechanism associated with a dark scalar boson. At…
This article reports the first operation of a double-sided CMOS pixelated ladder in a collider experiment, namely in the inner tracker volume of the Belle II experiment during the Phase 2 run of the SuperKEKB collider. Design and…
We develop a self-supervised method for density-based anomaly detection using contrastive learning, and test it using event-level anomaly data from CMS ADC2021. The AnomalyCLR technique is data-driven and uses augmentations of the…
The Belle II experiment at the SuperKEKB accelerator is a next-generation B-factory aiming to collect 50 ab$^{-1}$, about 50 times the data collected at Belle, to study rare processes and make precision measurements that may expose physics…
The Belle II experiment has been preparing for its first e+ e- collisions, scheduled in April 2018. With a target luminosity 40 times greater than the Belle experiment, the goal of Belle II is to open the door to a panorama of measurements…
Anomaly detection in High Energy Physics requires identifying rare signals against overwhelming backgrounds, without prior knowledge of the signal. We present the first application of masked-token prediction, a technique from Large Language…
We apply several machine learning algorithms to the problem of anomaly detection in operational data for large-scale, high-voltage electric power grids. We observe important differences in the performance of the algorithms. Neural networks…