Results 61 to 70 of about 4,738,087 (364)
A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction [PDF]
IEEE International Conference on Computer Vision, 2021 In this paper, we propose HF2-VAD, a Hybrid framework that integrates Flow reconstruction and Frame prediction seamlessly to handle Video Anomaly Detection.
Zhian Liu +4 more
semanticscholar +1 more source
Nuclear Physics B, 2022 Anomaly detection algorithms have been proved to be useful in the search of new physics beyond the Standard Model. However, a prerequisite for using an anomaly detection algorithm is that the signal to be sought is indeed anomalous.
Ji-Chong Yang, Yu-Chen Guo, Li-Hua Cai
doaj
发电技术, 2021 Anomaly detection of gas turbine hot components can ensure its operational safety and reliability. With the boom of artificial intelligence, data-driven fault diagnosis is becoming increasingly popular.
Mingliang BAI +4 more
doaj +1 more source
Log-based Anomaly Detection Without Log Parsing [PDF]
International Conference on Automated Software Engineering, 2021 Software systems often record important runtime information in system logs for troubleshooting purposes. There have been many studies that use log data to construct machine learning models for detecting system anomalies.
Van-Hoang Le, Hongyu Zhang
semanticscholar +1 more source
Dendritic Cells for Anomaly Detection [PDF]
SSRN Electronic Journal, 2006 Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrusion detection system based on a novel concept in immunology, the Danger Theory.
Greensmith, Julie +2 more
openaire +5 more sources
Anomaly Detection in Manufacturing
, 2023 AbstractThis chapter provides an introduction to common methods of anomaly detection, which is an important aspect of quality control in manufacturing. We give an overview of widely used statistical methods for detecting anomalies based on k-means, decision trees, and Support Vector Machines.
Scholz, Jona +3 more
openaire +1 more source
Q fever outbreak in the terraced vineyards of Lavaux, Switzerland
New Microbes and New Infections, EarlyView., 2014 Abstract Coxiella burnetii infection (Q fever) is a widespread zoonosis with low endemicity in Switzerland, therefore no mandatory public report was required. A cluster of initially ten human cases of acute Q fever infections characterized by prolonged fever, asthenia and mild hepatitis occurred in 2012 in the terraced vineyard of Lavaux ...
C. Bellini +9 more
wiley +1 more source
Anomaly detection by robust statistics [PDF]
WIREs Data Mining and Knowledge Discovery, 2017 Real data often contain anomalous cases, also known as outliers. These may spoil the resulting analysis but they may also contain valuable information. In either case, the ability to detect such anomalies is essential. A useful tool for this purpose is robust statistics, which aims to detect the outliers by first fitting the majority of the data and ...
Rousseeuw, Peter, Hubert, Mia
openaire +5 more sources
Predictive anomaly detection for marine diesel engine based on echo state network and autoencoder
Energy Reports, 2022 Marine diesel engine with high thermal efficiency and good economy has become the main power of ships. Anomaly detection is an important method to improve the operation reliability of marine diesel engine.
Chong Qu +3 more
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Network Anomaly Detection by Using a Time-Decay Closed Frequent Pattern
Information, 2019 Anomaly detection of network traffic flows is a non-trivial problem in the field of network security due to the complexity of network traffic. However, most machine learning-based detection methods focus on network anomaly detection but ignore the user ...
Ying Zhao +6 more
doaj +1 more source