Results 71 to 80 of about 4,738,087 (364)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Anomaly detection has become one of the crucial tasks in hyperspectral images processing. However, most deep learning-based anomaly detection methods often suffer from the incapability of utilizing spatial–spectral information, which decreases the
Song Xiao +5 more
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AGAD: Adversarial Generative Anomaly Detection [PDF]
arXiv, 2023 Anomaly detection suffered from the lack of anomalies due to the diversity of abnormalities and the difficulties of obtaining large-scale anomaly data. Semi-supervised anomaly detection methods are often used to solely leverage normal data to detect abnormalities that deviated from the learnt normality distributions.
arxiv
Video anomaly detection using Cross U-Net and cascade sliding window
Journal of King Saud University: Computer and Information Sciences, 2022 As video surveillance exponentially increases, a method that automatically detects abnormal events in video surveillance is essential. Several anomaly detection methods have been proposed to detect abnormal events in video surveillance. Much research has
Yujun Kim +3 more
doaj
Anomaly Detection with Partially Observed Anomalies [PDF]
Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018 In this paper, we consider the problem of anomaly detection. Previous studies mostly deal with this task in either supervised or unsupervised manner according to whether label information is available. However, there always exists settings which are different from the two standard manners.
Jun Zhou +4 more
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ASAD: Adaptive Seasonality Anomaly Detection Algorithm under Intricate KPI Profiles
Applied Sciences, 2022 Anomaly detection is the foundation of intelligent operation and maintenance (O&M), and detection objects are evaluated by key performance indicators (KPIs). For almost all computer O&M systems, KPIs are usually the machine-level operating data. Moreover,
Hao Wang +8 more
doaj +1 more source
Real-World Anomaly Detection in Surveillance Videos [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Surveillance videos are able to capture a variety of realistic anomalies. In this paper, we propose to learn anomalies by exploiting both normal and anomalous videos.
Waqas Sultani, Chen Chen, M. Shah
semanticscholar +1 more source
Hybrid Discriminator With Correlative Autoencoder for Anomaly Detection
IEEE Access, 2021 Advances in deep neural networks (DNNs) have led to impressive results and in recent years many works have exploited DNNs for anomaly detection. Among others, generative/reconstruction model-based methods have been frequently used for anomaly detection ...
Jungeon Lee +2 more
doaj +1 more source
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection [PDF]
arXiv, 2022 Despite most existing anomaly detection studies assume the availability of normal training samples only, a few labeled anomaly examples are often available in many real-world applications, such as defect samples identified during random quality inspection, lesion images confirmed by radiologists in daily medical screening, etc.
arxiv
Anomaly Detection for Bivariate Signals [PDF]
, 2019 The anomaly detection problem for univariate or multivariate time series is a critical question in many practical applications as industrial processes control, biological measures, engine monitoring, supervision of all kinds of behavior. In this paper we propose a simple and empirical approach to detect anomalies in the behavior of multivariate time ...
Cottrell, Marie +3 more
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Online Video Anomaly Detection
Sensors, 2023 With the popularity of video surveillance technology, people are paying more and more attention to how to detect abnormal states or events in videos in time. Therefore, real-time, automatic and accurate detection of abnormal events has become the main goal of video-based surveillance systems.
Yuxing Zhang +3 more
openaire +3 more sources