Results 11 to 20 of about 108,365 (267)
Toward Practical Crowdsourcing-Based Road Anomaly Detection With Scale-Invariant Feature
IEEE Access, 2019 Road anomaly detection with crowdsourced sensor data has become an increasingly important field of research over the last few years. Traditional ways for road anomaly detection are either threshold-based detection techniques or feature-based detection ...
Yuanyi Chen +3 more
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Pose‐driven human activity anomaly detection in a CCTV‐like environment
IET Image Processing, 2023 Human activity anomaly detection plays a crucial role in the next generation of surveillance and assisted living systems. Most anomaly detection algorithms are generative models and learn features from raw images.
Yuxing Yang +2 more
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Real-time Anomaly Detection Framework via System Calls Based on Integrated Learning [PDF]
Jisuanji gongcheng, 2023 Anomaly detection based on system calls data cannot complete the synchronous perception task of intrusion behavior within the process lifecycle，and there is a problem of low real-time anomaly detection accuracy.
CHEN Zhonglei, YI Peng, CHEN Xiang, HU Tao
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KAN-based Unsupervised Multivariate Time Series Anomaly Detection Network [PDF]
Jisuanji kexueTime series data is widely present in fields such as finance,healthcare,industry,and transportation.Time Series Ano-maly Detection(TSAD) is crucial for ensuring system stability and safety.Most current time series anomaly detection methods are ...
WANG Cheng, JIN Cheng
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Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System
Sensors, 2021 The biggest problem with conventional anomaly signal detection using features was that it was difficult to use it in real time and it requires processing of network signals.
Hoon Ko, Kwangcheol Rim, Isabel Praça
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Multivariate Time Series Anomaly Detection Algorithm in Missing Value Scenario [PDF]
Jisuanji kexueTime series anomaly detection is an important research field in industry.Current methods of time series anomaly detection focus on anomaly detection for complete time series data,without considering the time series anomaly detection task containing ...
ZENG Zihui, LI Chaoyang, LIAO Qing
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Machine Learning for Anomaly Detection: A Systematic Review
IEEE Access, 2021 Anomaly detection has been used for decades to identify and extract anomalous components from data. Many techniques have been used to detect anomalies. One of the increasingly significant techniques is Machine Learning (ML), which plays an important role
Ali Bou Nassif +3 more
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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
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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
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A Survey of AI-Based Anomaly Detection in IoT and Sensor Networks
Sensors, 2023 Machine learning (ML) and deep learning (DL), in particular, are common tools for anomaly detection (AD). With the rapid increase in the number of Internet-connected devices, the growing desire for Internet of Things (IoT) devices in the home, on our ...
Kyle DeMedeiros +2 more
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